Overview The ARIMA (AutoRegressive Integrated Moving Average) Indicator is a powerful tool used to forecast future price movements by combining differencing, autoregressive, and moving average components. This indicator is designed to help traders identify trends and potential reversal points by analyzing the historical price data. Key Features ...

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Library "math" It's a library of discrete aproximations of a price or Series float it uses Fourier Discrete transform, Laplace Discrete Original and Modified transform and Euler's Theoreum for Homogenus White noice operations. Calling functions without source value it automatically take close as the default source value. Here is a picture of Laplace and...

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Use this Strategy to Fine-tune inputs for the (W&)FSVZ0 Indicator. Strategy allows you to fine-tune the indicator for 1 TimeFrame at a time; cross Timeframe Input fine-tuning is done manually after exporting the chart data. I suggest using "Close all" input False when fine-tuning Inputs for 1 TimeFrame. When you export data to Excel/Numbers/GSheets I suggest...

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█ OVERVIEW This script presents an implementation of the digital smoothing filter introduced by John Ehlers in his article "The Ultimate Smoother" from the April 2024 edition of TASC's Traders' Tips . █ CONCEPTS The UltimateSmoother preserves low-frequency swings in the input time series while attenuating high-frequency variations and noise. The defining...

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Another useful indicator is here! Kalman Filter is a quantitative tool created by Rudolf E. Kalman. In the case of trading, it can help smooth out the price data that traders observe, making it easier to identify underlying trends. The Kalman Filter is particularly useful for handling price data that is noisy and unpredictable. As an adaptive-based algorithm, it...

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**NOTE: FOR COMPARISON TRADITIONAL ROC IS PLOTTED WITH THE SAME ROC LENGTH OF 9. IT IS NOT PART OF THE INDICATOR" The Nasan ROC indicator is smoothed version of the of the traditional ROC indicator. The Nasna ROC uses a triple pass moving average differencing strategy. A cumulative sum of the deviations obtained from the moving average differencing provides a...

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Ticker: AMEX:SPY , Timeframe: 1m, Indicator settings: default General Purpose This script is an upgrade to the classic Bollinger Bands. The idea behind Bollinger bands is the detection of price movements outside of a stock's typical fluctuations. Bollinger Bands use a moving average over period n plus/minus the standard deviation over period n times a...

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The " ATR Adaptive RSI Oscillator " is a versatile technical analysis tool designed to help traders make informed decisions in dynamic market conditions. It combines the Relative Strength Index (RSI) with the Average True Range (ATR) to provide adaptive and responsive insights into price trends. Key Features : Adaptive RSI Periods : The indicator introduces...

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The Discrete Fourier Transform Money Flow Index indicator integrates the Money Flow Index (MFI) with Discrete Fourier Transform (credit to author wbburgin - May 26 2023 ) smoothing to offer a refined and smoothed depiction of the MFI's underlying trend. The MFI is calculated using the formula: MFI = 100 - (100 / (1 + MR)), where a high MFI value indicates robust...

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The Data Sampling Indicator was created by John Ehlers (Stocks and Commodities Mar 2023) and this is a genius method to reduce noise in the market data but also doesn't introduce any lag while doing so. The way this works is because traditionally, people have always relied on the close price as the default input for many indicators such as the RSI or MACD as...

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This script utilizes its source from a non-repainting renko closing price. Renko charts focus solely on price movement and minimize the impacts of time and the extra noise time creates. Employing the renko close helps smooth out the Ichimoku Cloud. Insignificant price movements will not cause a change in the plotted lines of the indicator unless a new threshold...

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NET BSP derived from Buying & Selling Pressure which is a volatility indicator that monitors average metrics of green and red candles separately. We could navigate more confidently through market with projected market balance. BSP allowed us to track and analyze the ongoing performance of bullish and bearish impulsive waves and their corrections. Due to...

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Library "Library_Smoothers" CorrectedMA(Src, Len) CorrectedMA The strengths of the corrected Average (CA) is that the current value of the time series must exceed a the current volatility-dependent threshold, so that the filter increases or falls, avoiding false signals when the trend is in a weak phase. Parameters: Src Len Returns: The...

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This is my attempt at smoothing the exponential moving average any its cousins. I literally just smoothed the source and alpha and this is what we got. I really like this because you get a nice smooth yet fast acting moving average that works better than a traditional simple moving average. This script also included directional alerts. Smooth EMA Smooth...

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Introduction Hello community, here I applied the Inverse Fisher Transform, Ehlers dominant cycle determination and smoothing methods on a simple Rate of Change (ROC) indicator You have a lot of options to adjust the indicator. Usage The rate of change is most often used to measure the change in a security's price over time. That's why it is a momentum...

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Introduction This here is a non-repainting indicator where I use inverse Fisher transformation and smoothing on the well-known CCI (Commdity Channel Index) momentum indicator. "The Inverse Fisher Transform" describes the calculation and use of the inverse Fisher transform by Dr . Ehlers in 2004. The transform is applied to any indicator with a known probability...

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This is a combination of the Lux Algo Nadaraya-Watson Estimator and Envelope. Please note the repainting issue. In addition, I've added a plot of the actual values of the current barstate of the Nadaraya-Watson windows as they are computed (lines 92-95). It only plots values for the current data at each time update. It is interesting to compare the trajectory...

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What is Nadaraya–Watson Regression? Nadaraya–Watson Regression is a type of Kernel Regression, which is a non-parametric method for estimating the curve of best fit for a dataset. Unlike Linear Regression or Polynomial Regression, Kernel Regression does not assume any underlying distribution of the data. For estimation, it uses a kernel function, which is a...

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