Level: 2 Background John F. Ehlers introduced Adaptive BandPass Filter in his "Cycle Analytics for Traders" chapter 11 on 2013. Function Adaptive band-pass filter was designed. It just makes since to tune that filter to the measured dominant cycle to eliminate all the other frequency components that are of no interest. Here, the adaptive band-pass indicator...
Level: 2 Background John F. Ehlers introduced Adaptive CCI 2013 in his "Cycle Analytics for Traders" chapter 11 on 2013. Function The time length to be used for the channel in the calculations is widely varied in the literature. In all cases, the length is rather arbitrarily established to fit the indicator to some preconceived event. It seems to me that it...
Level: 2 Background John F. Ehlers introduced Adaptive RSI 2013 in his "Cycle Analytics for Traders" chapter 11 on 2013. Function The adaptive RSI starts with the computation of the dominant cycle using the autocorrelation periodogram approach. The identification of the RSI indicator itself following the dominant cycle calculation is noted by the comment near...
Level: 2 Background John F. Ehlers introduced DFT Spectral Estimate in his "Cycle Analytics for Traders" chapter 9 on 2013. Function The DFT is accomplished by correlating the data with the cosine and sine of each period of interest over the selected window period. The sum of the squares of each of these correlated values represents the relative power at each...
Level: 2 Background John F. Ehlers introduced Autocorrelation Reversals in his "Cycle Analytics for Traders" chapter 8 on 2013. Function One of the distinctive characteristics of autocorrelation is that the autocorrelation shifts from yelow to red or from red to yellow at all values of lag at the cyclic reversals of the price. Therefore, all we need do to...
Level: 2 Background John F. Ehlers introduced Autocorrelation Periodogram in his "Cycle Analytics for Traders" chapter 8 on 2013. Function Construction of the autocorrelation periodogram starts with the autocorrelation function using the minimum three bars of averaging. The cyclic information is extracted using a discrete Fourier transform (DFT) of the...
Level: 2 Background John F. Ehlers introduced Autocorrelation Indicator in his "Cycle Analytics for Traders" chapter 8 on 2013. Function If we correlate a waveform composed of perfectly random numbers by itself, the correlation will be perfect. However, if we lag one of the data streams by just one bar, the correlation will be dramatically reduced. In a long...
Level: 2 Background John F. Ehlers create Synthetic Prices Using Random Numbers with Memory in his "Cycle Analytics for Traders" chapter 8 on 2013. Function Peter Swerling is best known for the class of statistically “fluctuating target” scattering models he developed in the early 1950s to characterize the performance of pulsed radar systems, referred to as...
Level: 2 Background John F. Ehlers introuced Modified RSI Indicator in his "Cycle Analytics for Traders" chapter 7 on 2013. Function The RSI is the percentage of the sum of the delta closes up to the sum of all the delta closes over the observation period. The only variable here is the observation period. To have maximum effectiveness the observation period...
Level: 2 Background John F. Ehlers introuced Modified Stochastic Indicator in his "Cycle Analytics for Traders" chapter 7 on 2013. Function Conventional indicators are not immune to the effects of spectral dilation. For example, a Stochastic indicator remains near its upper bound when the market is in an uptrend even though a relatively short lookback period...
Level: 2 Background John F. Ehlers introuced Roofing Filter Indicator in his "Cycle Analytics for Traders" chapter 7 on 2013. Function The roofing filter does an excellent job of using only the frequency components between its upper and lower critical periods. All that needs to be done to create an indicator from the roofing filter is to add more generality...
Level: 2 Background John F. Ehlers introuced Zero Mean Roofing Filter in his "Cycle Analytics for Traders" chapter 7 on 2013. Function The HP-LP Roofing Filter output still contains all of these frequency components. The only way we can reduce the effect of these lower-frequency components is to introduce another high-pass filter, adding an additional 6 dB...
Level: 2 Background John F. Ehlers introuced HP-LP Roofing Filter in his "Cycle Analytics for Traders" chapter 7 on 2013. Function A “roofing filter” can be used to limit the frequency content of an input before proceeding to construct an indicator. The roofing filter is composed of a highpass filter that passes only frequency components whose periods are...
Level: 2 Background John F. Ehlers introuced Hurst Coefficient Indicator in his "Cycle Analytics for Traders" chapter 6 on 2013. Function The Hurst coefficient is one way to attempt to get a handle on the slope of the power density of market data. The Hurst coefficient varies between 0 and 1, and is related to the α power coefficient as H = 1 − α/2. The Hurst...
Level: 2 Background John F. Ehlers introuced Zero Crossings Period Measurer in his "Cycle Analytics for Traders" chapter 5 on 2004. Function The band-pass filter can be used as a relatively simple measurement of the dominant cycle. A cycle is complete when the waveform crosses zero two times from the last zero crossing. Therefore, each successive zero...
Level: 2 Background John F. Ehlers introuced Bandpass Filter in his "Cycle Analytics for Traders" chapter 5 on 2004. Function After declaring variables, the band-pass filter calculation is preceded by a high-pass filter whose cutoff frequency is one half-bandwidth octave below the lower-frequency critical frequency of the band-pass filter to avoid...
Level: 2 Background John F. Ehlers introuced Decycler Oscillator in his "Cycle Analytics for Traders" chapter 4 on 2004. Function A decycler oscillator is created by subtracting the output of a high-pass filter having a shorter cutoff period from the output of another high-pass filter having a longer cutoff period. This way, both elements have a zero in their...
Level: 2 Background John F. Ehlers introuced Decycler in his "Cycle Analytics for Traders" chapter 4 on 2004. Function The concept of a decycler is really pretty simple. The cyclic components are removed by the process of cancellation. If the high-pass filter output is subtracted from the input data, the residual only contains the low-frequency components....