About This is a simple indicator that takes into account two types of realized volatility: Close-Close and High-Low (the latter is more useful for intraday trading). The output of the indicator is two values / plots: an average of High-Low volatility minus Close-Close volatility (10day period is used as a default) the current value of the indicator When...

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Library "NormalDistributionFunctions" The NormalDistributionFunctions library encompasses a comprehensive suite of statistical tools for financial market analysis. It provides functions to calculate essential statistical measures such as mean, standard deviation, skewness, and kurtosis, alongside advanced functionalities for computing the probability density...

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The geometric moving average is a type of moving average that calculates the geometric mean of the previous n-periods of the price time series. Unlike the simple moving average that uses the arithmetic mean to continuously calculate the moving average as new price data comes in, the geometric moving average uses the geometric mean formula to get the moving average...

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Median of Means (MoM) is a measure of central tendency like mean (average) and median. However, it could be a better and robust estimator of central tendency when the data is not normal, asymmetric, have fat tails (like stock price data) and have outliers. The MoM can be used as a robust trend following tool and in other derived indicators. Median of means (MoM)...

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The Relational Quadratic Kernel Channel (RQK-Channel-V) is designed to provide more valuable potential price extremes or continuation points in the price trend. Example: Usage: Lookback Window: Adjust the "Lookback Window" parameter to control the number of previous bars considered when calculating the Rational Quadratic Estimate. Longer windows capture...

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Upgrade of the Average True Range default indicator by TradingView. It adds and plots a trailing mean to show periods of increased volatility more clearly. ATR TRAILING MEAN A trailing mean, also known as a moving average, is a statistical calculation used to smooth out data over time and identify trends or patterns in a time series. In our indicator, it...

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The Intraday Mean Reversion Indicator works well on certain stocks. It should be used for day trading stocks but need to be applied on the Day to Day timeframe. The logic behind the indicator is that stocks that opens substantially lower than yesterdays close, very often bounces back during the day and closes higher than the open price, thus the name Intraday...

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A basic statistic to describe "ranges". There are three inputs: - short range - long range - moving average length The output is a ratio of the short range to the long range. In the screenshot example, the short range is a single day (bar) and the long range is five days. A value near "1" would mean that every day entirely fills the five day range, and that a...

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Keltner Channel Bands These normally consist of: Keltner Channel Upper Band = EMA + Multiplier ∗ ATR Keltner Channel Lower Band = EMA − Multiplier ∗ ATR However instead of using ATR we are using RMA This gives us a much smoother take of the KCB We are also using 2 sets of bands built on 1 Moving average, this is a common set up for mean reversion...

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Markets tend to mean revert. This indicator plots a moving average from a higher time frame (type of MA and length selectable by the user). It then calculates standard deviations in two dimensions: - Standard deviation of move of price away from this moving average - Standard deviations of number of bars spent in this extended range The indicator plots a table...

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Library "normsinv" Description: Returns the inverse of the standard normal cumulative distribution. The distribution has a mean of zero and a standard deviation of one; i.e., normsinv seeks that value z such that a normal distribtuion of mean of zero and standard deviation one is equal to the input probability. Reference: github.com normsinv(y0)...

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Volatility is cyclical, after a large move up or down the market typically "ranges" during the next session. Directional order flow that enters the market during this subsequent session tends not to persist, this non-persistency of transactions leads to a non-trend day which is when I trade intraday reversionary strategies. This script finds trend days in BTC...

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The Ergodic Mean Deviation Indicator was created by William Blau and this is a hidden gem that takes the difference between the current price and it's exponential moving average and then double smooths the result to create this indicator. This double smoothing of course creates a lag that allows it to give off a sustained buy signal during a bullish trend and vice...

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1) Plot up to 8 moving averages or donchian channels. 2) Moving average types include SMA, EMA, Double EMA, Triple EMA, Quadruple EMA, Pentuple EMA, Zero-Lag EMA, Tillson's T3, Hull's MA, Smoothed MA, Weighted MA, Volume-Weighted MA. 3) Donchian channels can be plotted for a user specified period with upper and lower lines based on either A) highest and lowest...

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This indicator plots the 1, 2 and 3 standard deviations from the mean as bands of color (hot and cold). Useful in identifying likely points of mean reversion. Default mean is WMA 200 but can be SMA, EMA, VWMA, and VAWMA. Calculating the standard deviation is done by first cleaning the data of outliers (configurable).

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Introduction: This strategy is a modification of the “3-day Mean Reversion Strategy” from the book "High Probability ETF Trading" by Larry Connors and Cesar Alvarez. In the book, the authors discuss a high-probability ETF mean reversion strategy for a 1-day time-frame with these simple rules: The price must be above the 200 day SMA and below the 5 day SMA. ...

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I like trading the 1 minute and 3 minutes time-frames. I'm what is commonly called a "scalper". Long term investments yes, I have some, but for trading, I don't have neither the time, nor the patience to wait hours or days for my trade to be complete. This doesn't mean I discount the higher time-frames, no, I actually rely heavily on them. I found that EMAs do a...

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DESCRIPTION Pythagorean Means of Moving Averages 1. Calculates a set of moving averages for high, low, close, open and typical prices, each at multiple periods. Period values follow the Fibonacci sequence. The "short" set includes moving average having the following periods: 5, 8, 13, 21, 34, 55, 89, 144, 233, 377. The "mid" set includes moving average having...

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