Page 2 | Standarddevation — Indicators and Strategies

Volatility Ratio Adaptive RSX [Loxx]Volatility Ratio Adaptive RSX this indicator adds volatility ratio adapting and speed value to RSX in order to make it more responsive to market condition changes at the times of high volatility, and to make it smoother in the times of low volatility What is RSX? RSI is a very popular technical indicator, because it takes into consideration market speed, direction and trend uniformity. However, the its widely criticized drawback is its noisy (jittery) appearance. The Jurik RSX retains all the useful features of RSI, but with one important exception: the noise is gone with no added lag. Included: -Toggle on/off bar coloring

Standard deviation channel of linear regression distance [AbAh]The indicator calculates the distance between linear regression line and the data point (price) as a percentage , then calculates the standard deviation for the linear regression distance , then draw the channel of two lines depending on the values of standard deviation . ///////// How to use //////////////// 1 - for Best result , indicator should be used on 2H frame Time of less : like 1H or 30 min 2 - The upper line and the lower line, both play a role as a support and resistance area, when the price bounces from the upper zone or lower zone, there is a high probability that it will move to the other line. 3 - The price breakout of one of the lower or upper lines may indicate a major price movement coming in the direction of the breakout /////////////////////////////////////

STD Stepped Ehlers Optimal Tracking Filter MTF w/ Alerts [Loxx]STD Stepped Ehlers Optimal Tracking Filter MTF w/ Alerts is the traditional Ehlers Optimal Tracking Filter but with stepped price levels, access to multiple time frames, and alerts. What is Ehlers Optimal Tracking Filter? From "OPTIMAL TRACKING FILTERS" by John Ehlers: "Dr. R.E. Kalman introduced his concept of optimum estimation in 1960. Since that time, his technique has proven to be a powerful and practical tool. The approach is particularly well suited for optimizing the performance of modern terrestrial and space navigation systems. Many traders not directly involved in system analysis have heard about Kalman filtering and have expressed an interest in learning more about it for market applications. Although attempts have been made to provide simple, intuitive explanations, none has been completely successful. Almost without exception, descriptions have become mired in the jargon and state-space notation of the “cult”. Surprisingly, in spite of the obscure-looking mathematics (the most impenetrable of which can be found in Dr. Kalman’s original paper), Kalman filtering is a fairly direct and simple concept. In the spirit of being pragmatic, we will not deal with the full-blown matrix equations in this description and we will be less than rigorous in the application to trading. Rigorous application requires knowledge of the probability distributions of the statistics. Nonetheless we end with practically useful results. We will depart from the classical approach by working backwards from Exponential Moving Averages. In this process, we introduce a way to create a nearly zero lag moving average. From there, we will use the concept of a Tracking Index that optimizes the filter tracking for the given uncertainty in price movement and the uncertainty in our ability to measure it." Included: -Standard deviation stepping filter, price is required to exceed XX deviations before the moving average line shifts direction -Selection of filtering based on source price, the moving average, or both; you can also set the Filter deviations to 0 for no filtering at all -Toggle on/off bar coloring -Toggle on/off signals -Long/Short alerts

STD Aadaptive, floating RSX Dynamic Momentum Index [Loxx]STD Aadaptive, floating RSX Dynamic Momentum Index is an attempt to improve Chande's original work on Dynamic Momentum Index. The full name of this indicator is "Standard-Deviation-Adaptive, floating-level, Dynamic Momentum Index on Jurik's RSX". What Is Dynamic Momentum Index? The dynamic momentum index is used in technical analysis to determine if a security is overbought or oversold. This indicator, developed by Tushar Chande and Stanley Kroll, is very similar to the relative strength index (RSI). The main difference between the two is that the RSI uses a fixed number of time periods (usually 14), while the dynamic momentum index uses different time periods as volatility changes, typically between five and 30. What is RSX? RSI is a very popular technical indicator, because it takes into consideration market speed, direction and trend uniformity. However, the its widely criticized drawback is its noisy (jittery) appearance. The Jurk RSX retains all the useful features of RSI, but with one important exception: the noise is gone with no added lag. Differences RSX is used instead of RSI for the calculation, producing a much smoother result Standard deviation is used to adapt the RSX calculation Floating levels are used instead of fixed levels for OB/OS Included -Change bar colors

Jurik Filter [Loxx]Jurik Filter is a Jurik-filtered moving average that acts as both a baseline and a support and resistance indicator What is Jurik Volty used in the Juirk Filter? One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive. What is the Jurik Moving Average? Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines. Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun. Included -Advanced filtering system using multiples of standard deviation, this filter acts paint dynamic support and resistance levels on the chart based on volatility -Double Jurik filtering -Toggle bar color on/off

DataCleaner Library "DataCleaner" Functions for acquiring outlier levels and acquiring a cleaned version of a series. outlierLevel(src, len, level) Gets the (standard deviation) outlier level for a given series. Parameters: src : The series to average and add a multiple of the standard deviation to. len : The The number of bars to measure. level : The positive or negative multiple of the standard deviation to apply to the average. A positive number will be the upper boundary and a negative number will be the lower boundary. Returns: The average of the series plus the multiple of the standard deviation. cleanUsing(src, result, len, maxDeviation) Returns an array representing the result series with (outliers provided by the source) removed. Parameters: src : The source series to read from. result : The result series. len : The maximum size of the resultant array. maxDeviation : The positive or negative multiple of the standard deviation to apply to the average. A positive number will be the upper boundary and a negative number will be the lower boundary. Returns: An array containing the cleaned series. clean(src, len, maxDeviation) Returns an array representing the source series with outliers removed. Parameters: src : The source series to read from. len : The maximum size of the resultant array. maxDeviation : The positive or negative multiple of the standard deviation to apply to the average. A positive number will be the upper boundary and a negative number will be the lower boundary. Returns: An array containing the cleaned series. outlierLevelAdjusted(src, level, len, maxDeviation) Gets the (standard deviation) outlier level for a given series after a single pass of removing any outliers. Parameters: src : The series to average and add a multiple of the standard deviation to. level : The positive or negative multiple of the standard deviation to apply to the average. A positive number will be the upper boundary and a negative number will be the lower boundary. len : The The number of bars to measure. maxDeviation : The optional standard deviation level to use when cleaning the series. The default is the value of the provided level. Returns: The average of the series plus the multiple of the standard deviation.