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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.
Pine Script® göstergesi
oquant tarafından
2
Intrabar BoxPlotThe Intrabar BoxPlot publication highlights an uncommon technique by displaying statistical intrabar Lower Timeframe (LTF) values on the chart. 🔶 USAGE 🔹 Middle 50% Boxes By showing the middle 50% intrabar values through a box, we can more easily see where the intrabar activity is mainly situated. The middle 50% intrabar values are referred to from here on as Interquartile range (IQR). In this example, the successive IQRs form a channel where the price eventually breaks out. Disproportionately distributed values can give insights which can be used to find potential support/resistance areas. IQR gaps can give valuable information as well. Potentially, the price can return to these gaps. Seeing the IQR areas against regular candles gives an alternative image of the underlying price movements. 🔹 Highest volume Price level The script displays the price level with the highest volume situated, dependable on the user's source setting. Setting the source at 'close' will only display intrabar close values; the same goes for high, low, ... As seen in the above example, the volume levels can aid in finding support/resistance. 🔹 Median The location of the median off all intrabar values is displayed as a coloured dot: green when the close price is higher than the opening price and red if otherwise. The median can give valuable insights into price movements. 🔹 Outliers Medium (white dots) and extreme (white X) outliers, in combination with the IQR box, can help identify potential areas of interest. 🔹 Volume Delta When there is a discrepancy between the delta volume and direction of the candle, this will be displayed as follows: Green candle: when the sum of the volume of red intrabars is higher than the sum of the volume of green intrabars, the candle will be coloured orange. Red candle: when the sum of the volume of green intrabars is higher than the sum of the volume of red intrabars, the candle will be coloured blue. 🔹 Highlight Boxplot only Probably the easiest way to display boxplot only is by changing the Bar's style to Bars . 🔶 DETAILS All intrabar values (Lower TimeFrame - LTF) are sorted and evaluated. Values can be close , high , low , ... by selecting this in Settings ( source ). The middle 50% of all values are displayed as a box; this contains the values between percentile 25 (p25) and percentile 75 (p75). The value of percentile rank 75 means 75% of all values are lower. The value of percentile rank 25 means 25% of all values are lower, or 75% is higher. The difference between p75 and p25 is also known as Interquartile range (IQR) IQR is used to check for outliers. Wiki: Boxplot , Interquartile range Extreme high: maximum value, higher than p75 + IQR*3 Max outlier high: maximum value, higher than p75 + IQR*1.5 but lower than p75 + IQR*3 Max: maximum value, lower than p75 + IQR*1.5 Min: minimum value, higher than p25 - IQR*1.5 Min outlier low: minimum value, lower than p25 - IQR*1.5 but higher than p25 - IQR*3 Extreme low: minimum value, lower than p25 - IQR*3 Max and min must not be interpreted with the current candle high/low. 🔹 Example: Length of chart-puppets The following example can make it easier to digest. Forty "chart-puppets" are sorted by their length. The p25 value is 97 The p50 value is 120 The p75 value is 149 75% of all "chart-puppets" are smaller than p75, and 25% is larger than p75. 50% of all "chart-puppets" are smaller than p50, and 50% is larger than p50 (= median). 25% of all "chart-puppets" are smaller than p25, and 75% is larger than p25. IQR = 149 - 97 = 52 Extreme outlier limit max: p75 + IQR*3 = 149 + 52*3 = 305 Mild outlier limit max: p75 + IQR*1.5 = 149 + 52*1.5 = 227 Mild outlier limit min: p25 - IQR*1.5 = 97 - 52*1.5 = 19 Extreme outlier limit min: p25 - IQR*3 = 97 - 52*3 = -59 In this example there are no outliers to be found, all values are located between p25 - IQR*1.5 (19) and p75 + IQR*1.5. (227) 🔹 Source settings Note that results are dependable on the chosen source (settings). When, for example, close is chosen as the source, only intrabar close prices are included. This means a low or high can stretch further then the min or max. Here we can see different results with different source settings 🔹 LTF settings When 'Auto' is enabled (Settings, LTF), the LTF will be the nearest possible x times smaller TF than the current TF. When 'Premium' is disabled, the minimum TF will always be 1 minute to ensure TradingView plans lower than Premium don't get an error. Examples with current Daily TF (when Premium is enabled): 500 : 3 minute LTF 1500 (default): 1 minute LTF 5000: 30 seconds LTF (1 minute if Premium is disabled) 🔶 SETTINGS Source: Set source at close, high, low,... 🔹 LTF LTF: LTF setting Auto + multiple: Adjusts the initial set LTF Premium: Enable when your TradingView plan is Premium or higher 🔹 Intrabar Delta : Colors, dependable on different circumstances. Up: Price goes up, with more bullish than bearish intrabar volume. Up-: Price goes up, with more bearish than bullish intrabar volume. Down: Price goes down, with more bearish than bullish intrabar volume. Down+: Price goes down, with more bullish than bearish intrabar volume. 🔹 Table Show table: Show details at the top right corner Show TF: Show LTF at the bottom right corner Text color/table size See DETAILS for more information
Pine Script® göstergesi
fikira tarafından
11
Trend Shift ProThe indicator is designed to identify shifts or changes in trends as blocks, the indicator's focus on analyzing the Median of Means, Interquartile Range, and Practical Significance for potential trend changes in the market using non parametric Cohen's D. The script is designed to operate on blocks of 21 bars. The key parts of the script related to this are the conditions inside the "if" statements: The bar_index % 21 == 0 condition checks if the current bar index is divisible by 21, meaning it's the beginning of a new block of 21 bars. This condition is used to reset and calculate new values at the start of each block. Therefore, signals or calculations related to the median of means (MoM), interquartile range (IQR), and Cohen's D are updated and calculated once every 21 bars. What this means is the frequency of signals is shown once every 21 bars. Price Movements of Blocks: Block-Based Analysis: This approach divides the price data into blocks or segments, often a fixed number of bars or candles. Each block represents a specific interval of time or price action. It involves No Smoothing: Unlike moving averages, block-based analysis does not apply any smoothing to the price data within each block. It directly examines the raw prices within each block. Let's break down the key concepts and how they are used for trading: Median of Means (MoM): The script calculates the median of the means of seven subgroups, each consisting of three bars in shuffled order. Each subgroup's mean is calculated based on the typical price (hlc3) of the bars within that subgroup. The median is then computed from these seven means, representing a central tendency measure. Note: The Median of Means provides a robust measure of central tendency, especially in situations where the dataset may have outliers or exhibit non-normal distribution characteristics. By calculating means within smaller subgroups, the method is less sensitive to extreme values that might unduly influence the overall average. This can make the Median of Means more robust than a simple mean or median when dealing with datasets that have heterogeneity or skewed distributions. Interquartile Range (IQR): The script calculates the IQR for each block of 21 bars. The IQR is a measure of statistical dispersion, representing the range between the first quartile (Q1) and the third quartile (Q3) of the data. Q1 and Q3 are calculated from the sorted array of closing prices of the 21 bars. Non-Parametric Cohen's D Calculation: Cohen's D is a measure of effect size, indicating the standardized difference between two means. In this script, a non-parametric version of Cohen's D is calculated, comparing the MoM values of the current block with the MoM values of the previous block. The calculation involves the MoM difference divided by the square root of the average squared IQR values. Practical Significance Threshold: The user can set a threshold for practical significance using the Threshold input. The script determines practical significance by comparing the calculated Cohen's D with this threshold. Plotting: The script plots the MoM values using both straight lines and circles, with the color of the circles indicating the direction of the MoM change (green for upward, red for downward, and blue for no change). Triangular shapes are plotted when the absolute value of Cohen's D is less than the practical significance threshold. Overall Purpose for Trading: The indicator is designed to help traders identify potential turning points or shifts in market sentiment. and use it as levels which needs to be crossed to have a new trend. Changes in MoM, especially when accompanied by practical significance as determined by Cohen's D, may signal the start of a new trend or a significant move in the market. Traders using this indicator would typically look for instances where the MoM values and associated practical significance suggest a high probability of a trend change, providing them with potential entry or exit signals. It's important for users to backtest and validate the indicator's effectiveness in different market conditions before relying on it for trading decisions.
Pine Script® göstergesi
federalTacos5392b tarafından
Rolling summaryStatistical methods based on mean cannot be effective all the time when attributed to financial data since it doesn't usually follow normal distribution, the data can be skewed or/and have extreme values which can be described as outliers. In order to deal with this problem it is appropriate to use median-based techniques. The most common one is called five-number summary/box plot, which plots median of the dataset, 25th (Q1) & 75th (Q3) percentiles (the medians of lower & upper parts of the original dataset divided by the original median), and whiskers calculated by taking range between Q1 and Q3, multiplying it by 1.5 and adding it to Q3 and subtracting it from Q1. The values which are outside the whiskers are considered outliers. Default settings of the script correspond to the classic box plot. Seven-number summary can be also plotted by this script, by turning on 4 additional percentiles/Bowley’s seven-figure summary by turning on first 2 additional percentiles and changing their values to 10 and 90 respectively. P.S.: Mean can be also turned in just to check the difference.
Pine Script® göstergesi
gorx1 tarafından
11