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It is my pleasure to welcome John Ehlers for a special webinar as part of our 4-year anniversary on nexusfi.com (formerly BMT). The webinar will be on Wednesday, June 12th @ 4:30 PM Eastern US.
Topics include:
- Market Data is Fractal in nature
- Spectral Dilation describes data over the full range of cycles
- Aliasing noise swamps shorter wave data
- Aliasing noise is best removed using a SuperSmoother filter
- Spectral Dilation effects are mitigated by a Roofing filter
- Price turning points must be anticipated for effective trading
- Trading System Performance is best valuated using Monte Carlo
As part of our special 4-year anniversary, we will be giving away (10) autographed copies of "MESA and Trading Market Cycles" by John Ehlers during the webinar. These will be given away during the live presentation.
More on John Ehlers and his new StockSpotter project: StockSpotter
More on nexusfi.com (formerly BMT)'s 4-year anniversary and 15 very special events during June with over $10,000 of prizes:
In just a few days, on June 10th, Big Mike Trading will turn 4 years old!
:partywave:
I am extremely proud of the community and everything that we've worked so hard to accomplish together. To say thanks to everyone for a fantastic 4-years, I have …
I am afraid that the Butterworth and the Super Smoother Filters are not exactly the same. Both of them were presented by John F.Ehlers, but they are bit different.
Below you will find the 2-pole and 3-pole Super Smoother Filter, so you …
@Big Mike: Unfortunately I did not have the time to attend the webinar this evening, although I admire the work of John Ehlers. I am the proud owner of one of his books, and have read many articles he has published in Technical Analysis of Stocks & Commodities. I also recommend to download the technical papers, which can be found on his website:
The four filters above can be selected as input for Bollinger Bands, Keltner Channels, smoothed Heikin Ashi Bars, the SuperTrend, the GannHiLoActivator and the MACD, see
The LBR 3/10 oscillator is a MACD built from SMAs. Calculate the difference from a 3-period and a 10-period simple moving average. This is the oscillator line. Then calculate a 16-period simple moving average from the oscillator line. This is the signal …
(not yet in the download section)
I have also used the Distant Coefficient Filter as default option for smoothing the Balance of Power indicator by Igor
Livshin.
I have already reviewed the indicator, as I did not like the simple moving average. I think that the indicator has a better usability, if a different way of smoothing is used. I have therefore added the box with the 27 moving averages to apply to the …
A collection of Ehlers indicators
I have further adapted a set of Ehlers indicators which were coded for NT 6.5 to run with NT 7.0. I am not the author of the code though and cannot guarantee that the indicators have been correctly implemented. The collection includes
And then there are a few indicators that were published in the Trader's Tips of Technical Analysis of Stocks & Commodities, which I have not found in this forum (attached below)
Finally, there is still an unresolved problem relating to the Sinewave Oscillator. The original formula in the book does not work with all instruments, the eSignal formula shown in the book is not a 1:1 translation from the original TradeStation code, and it seems that all adaptions of this indicator to different software packages are variations of the original indicator.
Most of the versions of the Hilbert Sinewave Oscillator, which I have seen are flawed. The formula used by John Ehlers is complex - see his book "Cybernetic Analysis for Stocks and Futures" pp 154,155, and the translation to eSignal by his partner …
All of this adds up to an impressive collection of tools for technical analysis. John Ehlers, thank you very much for your contributions!
John Ehlers described his Roofing filter today in detail. When you have some time available to watch the recording, which I will post shortly, and to code up the indicator, I know it would be helpful to many.