Frequency

Return Dispersion Matrix [The Quant Science]Introduction The Return Dispersion Matrix is a quantitative analysis tool that maps the temporal dependence of returns. In technical terms, performs a two-dimensional, 1-lag autocorrelation analysis, measuring the relationship and relative frequency between the return of the previous session (Yesterday) and that of the current session (Today) within specific volatility ranges. It answers the key questions: 💭 🔑 “When a candle closes in the green or red, what is the most common range of re

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by thequantscience

Volume Acceptance Zones [BigBeluga]Volume Acceptance Zones is a market structure tool designed to identify areas of price acceptance and statistically stretched extremes. By modeling market activity as a continuous distribution, the indicator highlights where price is actively accepted versus where it behaves as a statistical outlier. The goal is not prediction, but context — separating balanced price behavior from structurally stretched conditions. 🔵 CONCEPTS The indicator calculates a Volume-Weighted Balance Price ,

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Harmonic Resonance Field [JOAT]Harmonic Resonance Field Introduction The Harmonic Resonance Field is an open-source overlay indicator that combines dynamic range detection, Renko-style trend tracking, harmonic frequency analysis, and magnetic field visualization into a unified system for identifying consolidation zones, trend direction, and potential reversal points. It is designed for traders who want to understand where price is within its current range, how strong the prevailing trend is, and when conditions are ripe

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by officialjackofalltrades

Rolling SSA Oscillator [LuxAlgo]The Rolling SSA Oscillator indicator is a cycle-analysis tool that utilizes Singular Spectrum Analysis (SSA) to decompose price action into its most significant periodic components, providing a real-time view of underlying market rhythms. Unlike traditional lagging oscillators, this script uses eigendecomposition to isolate dominant trends and noise-reduced oscillations for better market timing. 🔶 USAGE The indicator provides two primary components derived from the price's spectral signature

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HTF Frequency Zone [BigBeluga]🔵 OVERVIEW HTF Frequency Zone highlights the dominant price level (Point of Control) and the full high–low expansion of any higher timeframe — Daily, Weekly, or Monthly. It captures the frequency of closes inside each HTF candle and plots the most traded “frequency zone”, allowing traders to easily see where price spent the most time and where buy/sell pressure accumulated. This tool transforms each higher-timeframe bar into a fully visualized structure: • Top = HTF high • Bottom = HT

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Frequency Momentum Oscillator [QuantAlgo]🟢 Overview The Frequency Momentum Oscillator applies Fourier-based spectral analysis principles to price action to identify regime shifts and directional momentum. It calculates Fourier coefficients for selected harmonic frequencies on detrended price data, then measures the distribution of power across low, mid, and high frequency bands to distinguish between persistent directional trends and transient market noise. This approach provides traders with a quantitative framework for assessing

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Count █ OVERVIEW A library of functions for counting the number of times (frequency) that elements occur in an array or matrix. █ USAGE Import the Count library. import joebaus/count/1 as c Create an array or matrix that is a `float`, `int`, `string`, or `bool` type to count elements from, then call the count function on the array or matrix. id = array.from(1.00, 1.50, 1.25, 1.00, 0.75, 1.25, 1.75, 1.25) countMap = id.count() // Alternatively: countMap = c.count(id) The "count map" w

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Deviation Trend Profile [BigBeluga]🔵 OVERVIEW A statistical trend analysis tool that combines moving average dynamics with standard deviation zones and trend-specific price distribution. This is an experimental indicator designed for educational and learning purposes only. 🔵 CONCEPTS Trend Detection via SMA Slope: Detects trend shifts when the slope of the SMA exceeds a ±0.1 threshold. Standard Deviation Zones: Calculates ±1, ±2, and ±3 levels from the SMA using ATR, forming dynamic envelopes around the mean.

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Adaptive Resonance Oscillator [AlgoAlpha]Introducing the Adaptive Resonance Oscillator , an advanced momentum-based oscillator designed to dynamically adjust to changing market conditions. This innovative indicator detects market frequency through a Hilbert Transform approach, adapting in real-time to identify overbought and oversold conditions with improved accuracy. With built-in divergence detection, trend analysis, and customizable smoothing, this tool is perfect for traders looking to refine their entries and exits based on adapt

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High/Low Location Frequency [LuxAlgo]The High/Low Location Frequency tool provides users with probabilities of tops and bottoms at user-defined periods, along with advanced filters that offer deep and objective market information about the likelihood of a top or bottom in the market. 🔶 USAGE There are four different time periods that traders can select for analysis of probabilities: HOUR OF DAY: Probability of occurrence of top and bottom prices for each hour of the day DAY OF WEEK: Probability of occurrence of top

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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 aver

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by MaglebySystems

Spectrum Library "Spectrum" This library includes spectrum analysis tools such as the Fast Fourier Transform (FFT). method toComplex(data, polar) Creates an array of complex type objects from a float type array. Namespace types: array Parameters: data (array) : The float type array of input data. polar (bool) : Initialization coordinates; the default is false (cartesian). Returns: The complex type array of converted data. method sAdd(data, value, end, start, step)

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Frequency and Volume Profile FREQUENCY & VOLUME PROFILE ⚪ OVERVIEW The Frequency and Volume Profile indicator plots a frequency or volume profile based on the visible bars on the chart, providing insights into price levels with significant trading activity. ⚪ USAGE ● Market Structure Analysis: Identify key price levels where significant trading activity occurred, which can act as support and resistance zones. ● Volume Analysis: Use the volume mode to understand where the highest trading volumes have occurr

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Price Scenarios - The Quant Science GENERAL OVERVIEW Price Scenarios - The Quant Science is a quantitative statistical indicator that provides a forecast probability about future prices moving using the mathematical-statistical formula of statistical probability and expected value. HOW TO USE The indicator displays arrow-shaped signals that represent the probable future price movement calculated by the indicator, including the current percentage probability. Additionally, the candlesticks are colored based on the predict

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by thequantscience

Price Legs: Time & Distance. Measuring moves in time & price -Tool to measure price legs in terms of both time and price; gives an idea of frequency of market movements and their typical extent and duration. -Written for backtesting: seeing times of day where setups are most likely to unfold dynamically; getting an idea of typical and minimum sizes of small/large legs. -Two sets of editable lookback numbers to measure both small and large legs independently. -Works across timeframes and assets (units = mins/hours/days dependent on timeframe; units = '$' f

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FunctionPatternFrequency Library "FunctionPatternFrequency" Counts the word or integer number pattern frequency on a array. reference: rosettacode.org count(pattern) counts the number a pattern is repeated. Parameters: pattern : : array : array with patterns to be counted. Returns: array : list of unique patterns. array : list of counters per pattern. usage: count(array.from('a','b','c','a','b','a')) count(pattern) counts the number a pattern is repeated. Parameters: pattern

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by RicardoSantos

Fourier Extrapolator of Price w/ Projection Forecast [Loxx]Due to popular demand, I'm pusblishing Fourier Extrapolator of Price w/ Projection Forecast.. As stated in it's twin indicator, this one is also multi-harmonic (or multi-tone) trigonometric model of a price series xi, i=1..n, is given by: xi = m + Sum( a*Cos(w*i) + b*Sin(w*i), h=1..H ) Where: xi - past price at i-th bar, total n past prices; m - bias; a and b - scaling coefficients of harmonics; w - frequency of a harmonic ; h - harmonic number; H - total number of fitted harmoni

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Fourier Extrapolator of Price [Loxx]Fourier Extrapolator of Price is a multi-harmonic (or multi-tone) trigonometric model of a price series xi, i=1..n, is given by: xi = m + Sum( a *Cos(w *i) + b *Sin(w *i), h=1..H ) Where: xi - past price at i-th bar, total n past prices; m - bias; a and b - scaling coefficients of harmonics; w - frequency of a harmonic; h - harmonic number; H - total number of fitted harmonics. Fitting this model means finding m, a , b , and w that make the modeled values to be close to r

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FunctionBestFitFrequency Library "FunctionBestFitFrequency" TODO: add library description here array_moving_average(sample, length, ommit_initial, fillna) Moving Average values for selected data. Parameters: sample : float array, sample data values. length : int, length to smooth the data. ommit_initial : bool, default=true, ommit values at the start of the data under the length. fillna : string, default='na', options='na', '0', 'avg' Returns: float array errors: length > sample size "Canot call array

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by RicardoSantos

Candle Body Shapes Experimental: displays the frequency of candle types. reference: its a exploration of this topic: www.elitetrader.com

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by RicardoSantos

Tesla Coil This indicator reads the charts as frequency because the charts are just waves after all. This is an excellent tool for finding "Booms" and detecting dumps. Booms are found when all the frequencies pull under the red 20 line. Dumps are detected when all the lines drag themselves along the 20 line as seen is screenshots below. Below is another 2 examples of a "boom". Everything sucks in before exploding out. Below is an example of a dump:

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Fourier Analysis and Filtering [tbiktag]This tool uses Fourier transform to decompose the input time series into its periodic constituents and seasonalities , in other words, its frequency components . It also can reconstruct the time-domain data while using only the frequency components within a user-defined range (band-pass filtering). Thereby, this tool can reveal the cyclical characteristics of the studied market. USAGE The source and the size of the input data can be chosen by the “ Dataset Source ” and “ Dataset Size ” opti

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Particle Physics Moving Average This indicator simulates the physics of a particle attracted by a distance-dependent force towards the evolving value of the series it's applied to. Its parameters include: The mass of the particle The exponent of the force function f=d^x A "medium damping factor" (viscosity of the universe) Compression/extension damping factors (for simulating spring-damping functions) This implementation also adds a second set of all of these parameters, and tracks 16 particles evenly interpolat

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Filter Amplitude Response Estimator - A Simple Calculation In digital signal processing knowing how a system interact with the frequency content of an input signal is extremely important, the mathematical tool that give you this information is called "frequency response". The frequency response regroup two elements, the amplitude response, and the phase response. The amplitude response tells you how the system modify the amplitude of the frequency components in the input signal, the phase response tells you how the system modify the phase of the frequen

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