The Spectrum Derived Filter Bank was created by John Ehlers (Stocks & Commodities V. 26:3 (16-22)) and this is technically two indicators in one. This will let you know the current cycle period which is in blue and the other indicator will let you know if you should buy the stock or not. Buy when it is green and sell when it is red. Let me know if you would like...
The Dominant Cycle Tuned Bypass Filter was created by John Ehlers (Stocks & Commodities V. 26:3 (16-22)) and this is a particularly unique indicator because this does a pretty good job at predicting the future stock movements. If the blue line crosses over the red then a few bars from now the stock price will most likely go up and if the blue line crosses below...
The Swiss Army Knife Indicator was created by John Ehlers (Stocks & Commodities V. 24:1 (28-31, 50-53)) and it is 9 different filters in one big mega indicator! This is my first attempt at allowing you all to select different timeframes, to choose if you allow repainting or not, or by letting you choose which indicator you want to see on the chart. I know this may...
作品: 擺盪濾波器 (Swing Filter) This is a Swing Filter, the function is to remind you that you do not need to trade during the neutral period, only buy or long when the series is higher than the high-level you set, when the series is lower than the low-level you set, you need to short or hedge. Hope your to use it happily. In a larger time frame, the length can be set...
Price smoothed by a Kalman filter to cutout noisy price.
I've created this as a confirmation indicator to help know when market conditions are favorable to enter a trade. It measures volume, volatility, and ATR. It is not intended to tell you when to enter/exit the market, but use it with another indicator such as the mirror macd to filter out many losses and avoid entering the market during low volume or excessive...
When designing filters it can be interesting to have information about their characteristics, which can be obtained from the set of filter coefficients (weights). The following script analyzes the impulse response of a filter in order to return the following information: Lag Smoothness via the Herfindahl index Percentage Overshoot Percentage Of Positive...
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...
Removing irregular variations in the closing price remain a major task in technical analysis, indicators used to this end mostly include moving averages and other kind of low-pass filters. Understanding what kind of variations we want to remove is important, irregular (noisy) variations have mostly a short term period, fully removing them can be complicated if the...
Today we'll link time series forecasting with signal processing in order to provide an original and funny trend forecasting method, the post share lot of information, if you just want to see how to use the indicator then go to the section "Using The Indicator". Time series forecasting is an area dealing with the prediction of future values of a series by using a...
Time Series Lag Reduction Filter by Cryptorhythms Description A little filter to reduce lag on any time series data. Here we use an EMA to demonstrate how it works, but you could use it in many different ways/appications. This method can cause overshoot if you get too aggressive with the "lagReduce" setting. In this case lower the lagReduce variable. 👍 We...
This is an experimental study built on the concept of using roofing filters on price data proposed by John Ehlers. Roofing filters are a type of bandpass filter conventionally used in HF radio receivers in the first IF stage to limit the frequency spectrum passed on to later stages in the receiver. The goal in applying roofing filters to a price signal is to...
This is an experimental study designed to attenuate higher frequency oscillations in price and volatility with minimal lag. In this study, a single pole low pass filter is used. The low pass filter's cutoff period is determined either by a fixed user input, or by using an Instantaneous Frequency Measurement (IFM) algorithm. Most radar warning, electronic...
Introduction Remember that we can make filters by using convolution, that is summing the product between the input and the filter coefficients, the set of filter coefficients is sometime denoted "kernel", those coefficients can be a same value (simple moving average), a linear function (linearly weighted moving average), a gaussian function (gaussian filter), a...
This is Keltner Channel where I added Bull and Bear signals. It has a lot of settings to play around with. Have fun... For more information on Keltner Channel: www.investopedia.com
This is a potential solution to dealing with the inherent lag in most filters especially with instruments such as BTC and the effects of long periods of low volatility followed by massive volatility spikes as well as whipsaws/barts etc. We can try and solve these issues in a number of ways, adaptive lengths, dynamic weighting etc. This filter uses a non linear...
This is my first attempt at producing a strategy in Pine Script. I am NOT a professional coder. I'm not even a good coder at that. I've only started Pine Script coding since September 2019. I am teaching myself. This script is far from finished. I need to tweak a number of things about this script. Namely: Add a validity window to the 'trigger bar' condition....
Introduction The estimation of a least squares moving average of any degree isn't an interesting goal, this is due to the fact that lsma of high degrees would highly overshoot as well as overfit the closing price, which wouldn't really appear smooth. However i proposed an estimate of an lsma of any degree using convolution and a new sine wave series, all the...