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Scaling

Auto Center ChartAutomatically centers the chart within the current visible chart window. This utility indicator scans the visible range to determine its High and Low, then adjusts autoscale so that the most recent completed candle remains visually centered — without drawing any visible objects or cluttering the chart. Why This Is Useful: - Prevents price from hugging the top or bottom of the screen - Reduces visual bias during analysis - Improves clarity when planning risk/reward - Keeps the active candle visually balanced - Eliminates constant manual scale adjustments The script only influences scaling at the right edge and does not change when hovering over historical candles. Important Notes: - Requires Auto (fits data to screen) to be enabled in chart settings - May not work as expected if other indicators are also forcing autoscale or adding extra chart space - Designed for standard time-based charts If another script modifies scaling or the chart is not in Auto mode, TradingView’s scaling engine can override this indicator.
אינדיקטור Pine Script®
מאת ‎OrdrFlow‎
Vector Radius PBR ScalingVector Radius PBR Scaling — √Price Geometric Chart Calibration WHAT THIS INDICATOR DOES This indicator calculates a theoretically derived PBR (Points Per Bar) scaling value based on the concept of √price space geometry. You select a swing high and low using date inputs, and it outputs PBR values that can be used with TradingView's chart scaling for experimental geometric analysis with circle and arc tools. It is designed for students and researchers of geometric market theory who want to explore how √price transformations affect chart scaling and circle geometry. THE CONCEPT Standard PBR divides the price range by the number of bars. This treats all price levels equally — a $100 move at $50 is handled the same as a $100 move at $50,000. This indicator explores an alternative approach: what if price is better understood as a radial distance from zero? In this theoretical framework, √Price represents the radius — the distance from zero to any price level. The difference √H - √L represents the distance a move covers in this curved space, which is not the same as taking the square root of the range √(H-L). The velocity through this space, measured per bar, produces a scaling factor that accounts for the absolute price level of the instrument. The formula explored is: PBR = ((√H - √L) / B) × Radius Where H is the high price, L is the low price, B is the number of bars, and Radius is either √H or √Mid depending on the mode selected. TWO MODES Impulse (× √H) scales by the outer radius, which is the maximum price reached during the swing. The theory suggests this may suit trending or impulsive market conditions where the high represents peak energy expression. Equilibrium (× √Mid) scales by the midpoint radius, where Mid = (H + L) / 2. The theory suggests this may suit ranging or consolidating conditions where balance around the centre of the move matters more than its extremes. WHY √H IS USED FOR BOTH UP AND DOWN LEGS In this geometric framework, √H represents the outer boundary of the swing regardless of direction. Whether price moved up to a high or down from a high, the maximum price level defines the largest radius of the system. This is analogous to how a pendulum's behaviour is governed by its maximum displacement, not its direction of travel. WHAT THIS DOES NOT DO This indicator does not predict where price will go. It does not identify support or resistance levels. It does not generate trading signals. It does not guarantee that circles or arcs will align with future price action. It does not replace proper risk management or trading discipline. Any observed alignments between geometric projections and actual price behaviour may be coincidental. Markets are influenced by fundamentals, sentiment, liquidity, and countless other factors that no geometric formula can fully capture. HOW TO USE (FOR RESEARCH) Add the indicator to your chart. Select start and end dates around a swing you want to study. Read the PBR values from the table. Experiment with entering the PBR into your chart scaling settings. Draw circles or arcs and observe. Do not treat any observations as predictive. TABLE OUTPUT The indicator displays the high, low, and mid prices of the selected range, the price range and bar count, the √H, √L, and √Mid values, the root speed (√H - √L) / B, and the final PBR for both Impulse and Equilibrium modes. WHO THIS IS FOR This is for researchers and students of geometric market analysis who want a tool to quickly calculate √price-based scaling values. It assumes familiarity with PBR scaling, square-the-range concepts, and circle or arc geometry on price charts. If you are not familiar with these concepts, this indicator will not be useful to you out of the box. It is not a plug-and-play trading tool. INDICATOR IN ACTION NOTES Works on all timeframes and all instruments. The formula uses absolute price levels, not just the range, so the same dollar move at different price levels produces different PBR values. This is a theoretical exploration, not a proven trading methodology. No representation is made about the accuracy, reliability, or profitability of any analysis derived from this tool. This is an educational tool for geometric research. It is not financial advice. Do not trade based solely on geometric projections. Always use proper risk management. DISCLAIMER: This indicator is strictly educational and experimental. It is based on geometric theory applied to price charts. It does not generate buy or sell signals, it does not predict future price movement, and it does not guarantee any outcome. Use at your own risk. Past geometric alignments do not imply future alignments. This is a research and study tool only.
אינדיקטור Pine Script®
מאת ‎geneclash‎
Multi-Ticker Anchored CandlesMulti-Ticker Anchored Candles (MTAC) is a simple tool for overlaying up to 3 tickers onto the same chart. This is achieved by interpreting each symbol's OHLC data as percentages, then plotting their candle points relative to the main chart's open. This allows for a simple comparison of tickers to track performance or locate relationships between them. > Background The concept of multi-ticker analysis is not new, this type of analysis can be extremely helpful to get a gauge of the over all market, and it's sentiment. By analyzing more than one ticker at a time, relationships can often be observed between tickers as time progresses. While seeing multiple charts on top of each other sounds like a good idea...each ticker has its own price scale, with some being only cents while others are thousands of dollars. Directly overlaying these charts is not possible without modification to their sources. By using a fixed point in time (Period Open) and percentage performance relative to that point for each ticker, we are able to directly overlay symbols regardless of their price scale differences. The entire process used to make this indicator can be summed up into 2 keywords, "Scaling & Anchoring". > Scaling First, we start by determining a frame of reference for our analysis. The indicator uses timeframe inputs to determine sessions which are used, by default this is set to 1 day. With this in place, we then determine our point of reference for scaling. While this could be any point in time, the most sensible for our application is the daily (or session) open. Each symbol shares time, therefore, we can take a price point from a specified time (Opening Price) and use it to sync our analysis over each period. Over the day, we track the percentage performance of each ticker's OHLC values relative to its daily open (% change from open). Since each ticker's data is now tracked based on its opening price, all data is now using the same scale. The scale is simply "% change from open". > Anchoring Now that we have our scaled data, we need to put it onto the chart. Since each point of data is relative to it's daily open (anchor point), relatively speaking, all daily opens are now equal to each other. By adding the scaled ticker data to the main chart's daily open, each of our resulting series will be properly scaled to the main chart's data based on percentages. Congratulations, We have now accurately scaled multiple tickers onto one chart. > Display The indicator shows each requested ticker as different colored candlesticks plotted on top of the main chart. Each ticker has an associated label in front of the current bar, each component of this label can be toggled on or off to allow only the desired information to be displayed. To retain relevance, at the start of each session, a "Session Break" line is drawn, as well as the opening price for the session. These can also be toggled. Note: The opening price is the opening price for ALL tickers, when a ticker crosses the open on the main chart, it is crossing its own opening price as well. > Examples In the chart below, we can see NYSE:MCD NASDAQ:WEN and NASDAQ:JACK overlaid on a NASDAQ:SBUX chart. From this, we can see NASDAQ:JACK was the top gainer on the day. While this was the case, it also fell roughly 4% from its peak near lunchtime. Unlike the top gainer, we can see the other 3 tickers ended their day near their daily high. In the explanations above, the daily timeframe is used since it is the default; however, the analysis is not constrained to only days. The anchoring period can be set to any timeframe period. In the chart below, you can observe the Daily, Weekly, and Monthly anchored charts side-by-side. This can be used on all tickers, timeframes, and markets. While a typical application may be comparing relevant assets... the script is not limited. Below we have a chart tracking COMEX:GCV2026 , FX:EURUSD , and COINBASE:DOGEUSD on the AMEX:SPY chart. While these tickers are not typically compared side-by-side, here it is simply a display of the capabilities of the script. Enjoy!
אינדיקטור Pine Script®
מאת ‎SamRecio‎
1
Robust Scaled Dema | OquantOverview The Robust Scaled DEMA indicator is a tool designed for traders seeking to identify potential trend directions in financial markets. It combines the smoothing capabilities of a Double Exponential Moving Average (DEMA) with a robust scaling mechanism to normalize the data, making it more resilient to outliers and extreme price movements. This scaling helps in generating long and short signals based on predefined thresholds, visualized through color-coded plots and bars. The indicator aims to provide a balanced view of market momentum, reducing the impact of noise while highlighting significant shifts in price behavior. Key Factors/Components DEMA (Double Exponential Moving Average): Serves as the core smoothing component, reducing lag compared to simple averages by emphasizing recent price action more effectively. Robust Scaling Mechanism: Utilizes statistical measures like median and interquartile range to normalize the DEMA values, ensuring the indicator is less sensitive to extreme values or price spikes. Thresholds: User-defined upper and lower levels that trigger long or short signals when the scaled DEMA crosses them. Visual Elements: Includes plotted lines for the scaled DEMA and thresholds, plus color-coded candlestick bars for intuitive interpretation. Alerts: Built-in conditions for notifying users of potential entry points for long or short positions. How It Works The indicator starts by applying a DEMA to the chosen price source to create a smoothed representation of the market's direction. This smoothed value is then scaled using a robust statistical approach that accounts for the distribution of recent DEMA values, centering it around a median and adjusting for variability to minimize the influence of outliers. The resulting scaled metric is compared against user-set upper and lower thresholds: crossing above the upper suggests a bullish momentum (long signal), while dipping below the lower indicates bearish conditions (short signal). A state variable tracks these conditions to color the chart accordingly, helping traders visualize regime changes. Optional alerts fire on transitions. For Who Is Best/Recommended Use Cases This indicator is ideal for traders who employ trend-following or momentum-based strategies and need tools that perform well in non-normal market conditions, such as during high volatility or in assets prone to spikes. Use cases include identifying entry/exit points in trending environments, confirming breakouts, or integrating into multi-indicator systems for added confirmation. Quantitative traders or those backtesting strategies will appreciate its customizable parameters for optimization. Settings and Default Settings Source: The price data input for calculations, such as close, open, high, or low. Default: close. DEMA Length: Controls the period for the DEMA smoothing; shorter values increase responsiveness but may add noise, longer ones provide more lag but smoother signals. Default: 25. Robust Scaling Length: Defines the lookback period for the scaling statistics; affects how adaptive the normalization is to recent data distributions. Default: 40. Upper Threshold: The level above which a long signal is triggered; higher values make signals rarer but potentially more reliable. Default: 0.5. Lower Threshold: The level below which a short signal is triggered; lower values allow for more aggressive bearish detection. Default: 0. Conclusion The Robust Scaled DEMA offers an outlier-resistant alternative to traditional moving average indicators, empowering traders to navigate volatile markets. By blending exponential smoothing with statistical robustness, it provides actionable insights into trend shifts while minimizing false positives from extreme events.. ⚠️ Disclaimer: This indicator is intended for educational and informational purposes only. Trading/investing involves risk, and past performance does not guarantee future results. Always test and evaluate indicators/strategies before applying them in live markets. Use at your own risk.
אינדיקטור Pine Script®
מאת ‎oquant‎
2
rate_of_changeLibrary "rate_of_change" // @description: Applies ROC algorithm to any pair of values. // This library function is used to scale change of value (price, volume) to a percentage value, just as the ROC indicator would do. It is good practice to scale arbitrary ranges to set boundaries when you try to train statistical model. rateOfChange(value, base, hardlimit)   This function is a helper to scale a value change to its percentage value.   Parameters:      value (float)      base (float)      hardlimit (int)   Returns: per: A float comprised between 0 and 100
ספריית Pine Script®
מאת ‎sleptongems‎
Trig-Log Scaled Momentum OscillatorTaylor Series Approximations for Trigonometry: 1. The indicator starts by calculating sine and cosine values of the close price using Taylor Series approximations. These approximations use polynomial terms to estimate the values of these trigonometric functions. Mathematical Component Formation: 2. The calculated sine and cosine values are then multiplied together. This gives us the primary mathematical component, termed as the 'trigComponent'. Smoothing Process: 3. To ensure that our indicator is less susceptible to market noise and more reactive to genuine price movements, this 'trigComponent' undergoes a smoothing process using a simple moving average (SMA). The length of this SMA is defined by the user. Logarithmic Transformation: 4. With our smoothed value, we apply a natural logarithm approximation. Again, this approximation is based on the Taylor expansion. This step ensures that all resultant values are positive and offers a different scale to interpret the smoothed component. Dynamic Scaling: 5. To make our indicator more readable and comparable over different periods, the logarithmically transformed values are scaled between a range. This range is determined by the highest and lowest values of the transformed component over the user-defined 'lookback' period. ROC (Rate of Change) Direction: 6. The direction of change in our scaled value is determined. This offers a quick insight into whether our mathematical component is increasing or decreasing compared to the previous value. Visualization: 7. Finally, the indicator plots the dynamically scaled and smoothed mathematical component on the chart. The color of the plotted line depends on its direction (increasing or decreasing) and its boundary values.
אינדיקטור Pine Script®
מאת ‎Uldisbebris‎
1
Feature ScalingLibrary "Feature_Scaling" FS: This library helps you scale your data to certain ranges or standarize, normalize, unit scale or min-max scale your data in your prefered way. Mostly used for normalization purposes. minmaxscale(source, min, max, length)   minmaxscale: Min-max normalization scales your data to set minimum and maximum range   Parameters:      source      min      max      length   Returns: res: Data scaled to the set minimum and maximum range meanscale(source, length)   meanscale: Mean normalization of your data   Parameters:      source      length   Returns: res: Mean normalization result of the source standarize(source, length, biased)   standarize: Standarization of your data   Parameters:      source      length      biased   Returns: res: Standarized data unitlength(source, length)   unitlength: Scales your data into overall unit length   Parameters:      source      length   Returns: res: Your data scaled to the unit length
ספריית Pine Script®
מאת ‎serkany88‎
1
Feature scalerFeature scaler | Pine Utilities series, ready to be used in "study-on-study" fashion | Includes min-max, normalization, standardization and unit length scaling. One and only source: en.wikipedia.org Endpoint inputs allow to set an interval of interest for min-max scaler. Can be (and should be) applied to other studies, or to the chart itself. In this example, I applied min-max scaling to weighted linear regression's slope values. Unfortunately, "All data" is still "experimental" and works only on charts where less than 5000 bars are available. max_bars_back() didn't help. Sup TV
אינדיקטור Pine Script®
מאת ‎gorx1‎
9