Periodic

Iterative Locally Periodic Envelope The Iterative Locally Periodic Envelope is a phase-conditioned kernel estimator with temporal locality and endogenous dispersion modeling, implemented as a Nadaraya–Watson estimator under a locally periodic kernel. The locally periodic kernel defines similarity through cyclical phase alignment modulated by temporal proximity. Observations contribute to the estimator based on both their position within a repeating cycle structure and their recency, emphasizing structural recurrence with sensitiv

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by SensitiveSuit

Iterative Periodic Envelope The Iterative Periodic Envelope is a phase-conditioned kernel estimator with endogenous dispersion modeling, implemented as a Nadaraya–Watson estimator under a canonical periodic kernel. The periodic kernel defines similarity through cyclical phase alignment rather than temporal proximity or multi-scale distance decay. Observations contribute to the estimator based on their position within a repeating cycle structure, emphasizing structural recurrence over linear time dependence. The indicator

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by SensitiveSuit

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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Selected Times V3-En Does the stock drop every Wednesday? Do March months always move similarly? Does the 1st week of the month behave differently? Do you ever say "it always makes this move in these months"? Don't you want to see more clearly whether it actually makes this move or not? Don't you want to see and test periodically repeating price patterns? 1. Problem Some stocks or crypto assets exhibit systematic behaviors on certain days, weeks, or months. But it's hard to see - everything is mixed together on

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by ExperiMentalist

Periodic Volume Time Velocity Profile This is the Periodic Volume Time Velocity Profile (PVTVP). It is an advanced professional profiling tool that goes beyond standard volume analysis by introducing Time and Velocity (Flow Rate) as profile dimensions. By analyzing high-resolution intra-bar data, it builds precise profiles for any custom period (Session, Day, Week, etc.), helping you understand not just *where* the market traded, but *how* it traded there. ## The 3 Dimens

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by AustrianTradingMachine

Periodic Volume Profile This indicator visualizes volume profiles that are dynamically anchored to market structure events, rather than fixed time intervals. It builds these profiles using high-resolution intra-bar data to provide a precise view of where value is established during critical market phases. Key Features: Event-Based Profile Anchoring: The indicator starts a new profile based on one of three user-selected events ('Profile Anchor'): Swing: A new profile begins when the 'impulse baseline' (derived from d

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by AustrianTradingMachine

ValueAtTime █ OVERVIEW This library is a Pine Script® programming tool for accessing historical values in a time series using UNIX timestamps . Its data structure and functions index values by time, allowing scripts to retrieve past values based on absolute timestamps or relative time offsets instead of relying on bar index offsets. █ CONCEPTS UNIX timestamps In Pine Script®, a UNIX timestamp is an integer representing the number of milliseconds elapsed since January 1, 1970, at 00:00:00 UT

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Periodic Linear Regressions [LuxAlgo]The Periodic Linear Regressions (PLR) indicator calculates linear regressions periodically (similar to the VWAP indicator) based on a user-set period (anchor). This allows for estimating underlying trends in the price, as well as providing potential supports/resistances. 🔶 USAGE The Periodic Linear Regressions indicator calculates a linear regression over a user-selected interval determined from the selected "Anchor Period". The PLR can be visualized as a regular linear regression (St

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Periodic Activity Tracker [LuxAlgo]The Periodic Activity Tracker tool periodically tracks the cumulative buy and sell volume in a user-defined period and draws the corresponding matching bars and volume delta for each period. Users can select a predefined aggregation period from the following options: Hourly, Daily, Weekly, and Monthly. 🔶 USAGE This tool provides a simple and clear way of analyzing volumes for each aggregated period and is made up of the following elements: Buy and sell volumes by period as red an

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Volume Forecasting [LuxAlgo]The Volume Forecasting indicator provides a forecast of volume by capturing and extrapolating periodic fluctuations. Historical forecasts are also provided to compare the method against volume at time t . This script will not work on tickers that do not have volume data. 🔶 SETTINGS Median Memory: Number of days used to compute the median and first/third quartiles. Forecast Window: Number of bars forecasted in the future. Auto Forecast Window: Set the forecast window so that the foreca

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Morphed Sine Wave Introduction If you rescale a sine wave to the price you will need to correlate it with it in order to show good results, today i present a different method that does not involve correlation to "morph" a sine wave to the price in order to provide forecast's and highlight market periodic patterns. Parameters length control the period of the sine wave, power control the "morphing" amount, if you see for example that the results are going nuts try to increase power , if the results are j

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Recursive Stochastic The Self Referencing Stochastic Oscillator The stochastic oscillator bring values in range of (0,100). This process is called Feature scaling or Unity-Based Normalization When a function use recursion you can highlights cycles or create smoother results depending on various factors, this is the goal of a recursive stochastic. For example : k = s(alpha*st+(1-alpha)*nz(k )) where st is the target source. Using inputs with different scale level can modify the result of the indicator dep

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