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Kde

Price Density Clouds [EXCAVO]Continuous Kernel-Density Map of Where Price Has Actually Traded The Price Density Clouds builds a smooth, continuous probability density of price over a lookback window and paints it as gradient clouds directly behind the candles. Dense, saturated clouds mark value zones - the equilibrium levels where the market has spent the most time and where price tends to stall and revert. Thin, transparent gaps mark inefficiency zones - levels price travels through quickly. A dashed POC line marks the
Индикатор
от EXCAVO
1
KDE Value Clouds [LuxAlgo]The KDE Value Clouds indicator is a quantitative tool that uses Kernel Density Estimation (KDE) to visualize the statistical distribution of price action, identifying high-density "Value Clouds" where the market has spent the most time. 🔶 USAGE The indicator highlights areas of price " fair value " by calculating the probability density of price across a user-defined lookback period. Traders can use these density clusters to identify significant support and resistance levels that are often i
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от LuxAlgo
1
Probability-Based Adaptive Detection🙏🏻 PBAD (Probability-Based Adaptive Detection) : adaptive control tool for outliers || novelty detection, made for worst case data & processes, for the highest time complexity O(n^2) compared with the alternatives (would be explained in a sec). Thresholds are completely data driven and axiomatic, no need in provided hyperparameters, are not learned or optimized. The method accepts multiple weights, e.g. both temporal and volatility weights. Method briefly explained (I can go deeper if any1 as
Индикатор
от gorx1
1
SuperTrend + Relative Volume (Kernel Optimized)Introducing our new KDE Optimized Supertrend + Relative Volume Indicator! This innovative indicator combines the power of the Supertrend indicator along with Relative Volume. It utilizes the Kernel Density Estimation (KDE) to estimate the probability of a candlestick marking a significant trend break or reversal. ❓How to Interpret the KDE %: The KDE % is a crucial metric that reflects the likelihood that the current candlestick represents a true break in the SuperTrend line, supported by a
Индикатор
от fluxchart
22
RSI (Kernel Optimized) | Flux Charts💎 GENERAL OVERVIEW Introducing our new KDE Optimized RSI Indicator! This indicator adds a new aspect to the well-known RSI indicator, with the help of the KDE (Kernel Density Estimation) algorithm, estimates the probability of a candlestick will be a pivot or not. For more information about the process, please check the "HOW DOES IT WORK ?" section. Features of the new KDE Optimized RSI Indicator : A New Approach To Pivot Detection Customizable KDE Algorithm Realtime RSI & KDE Dashboard
Индикатор
от fluxchart
34
MathStatisticsKernelDensityEstimationLibrary "MathStatisticsKernelDensityEstimation" (KDE) Method for Kernel Density Estimation kde(observations, kernel, bandwidth, nsteps) Parameters: observations : float array, sample data. kernel : string, the kernel to use, default='gaussian', options='uniform', 'triangle', 'epanechnikov', 'quartic', 'triweight', 'gaussian', 'cosine', 'logistic', 'sigmoid'. bandwidth : float, bandwidth to use in kernel, default=0.5, range=(0, +inf), less will smooth the data. nsteps : int, numb
Библиотека
от RicardoSantos
10