4.8 • 670 Ratings
🗓️ 1 April 2020
⏱️ 8 minutes
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Bill Dreiss talks about his interest in Elliot Wave analysis & the Fractal nature of markets, and how he successfully have used this approach since the 1970s.
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0:00.0 | One thing that caught my attention and the attention of a colleague of mine that I've been |
0:07.0 | working with was the work of Benoit Mandelbrot, fractal geometry. And there was a book came out |
0:14.0 | in the early 80s, I think, the fractal geometry of nature. And it was apparent from reading this that this had |
0:22.5 | application to modeling the markets. In fact, Mandelbrot's first paper that he published was on |
0:31.4 | the cotton market. And that sort of, that introduced the world that was in compilation by Paul Kootenar called the random character of stock market prices. |
0:43.2 | That really was the beginning of Mandelbrot's career in fractal geometry. |
0:47.9 | And of course, sometime later that we picked up on this, but we could see from this that it was applicable. |
0:55.8 | And of course, another approach that was also popular at the time was the Elliott Wave. |
1:02.2 | Robert Baxter had really developed a reputation by his work in that regard. |
1:08.2 | And so one of the things we were looking at is because the Elliott Wave is obviously |
1:13.3 | a fractal kind of approach where you have patterns within patterns, within patterns. |
1:20.3 | We thought, well, gee, I wonder if it would be possible to automate the Elliott Wave. |
1:24.6 | Well, the short answer is no, and the reason is simply that if you have the kind of restrictive |
1:31.7 | conditions that are invoked by the Elliott Wave, the market won't cooperate. |
1:37.0 | So you've got to do a lot of, you've got to essentially shoehorn the data into the model. |
1:42.0 | What I found, or what I found is that it was better to shoehorn or to |
1:46.6 | devise a model that fit the data. And what came out of that was what we designated the fractal |
1:54.4 | wave algorithm. And the fractal wave algorithm is essentially a method of deconstructing prices into a series of fractal patterns. |
2:05.1 | And once again, it's self-similar across scale, meaning that you have a short-term pattern that can be combined into a longer-term pattern, which can be combined in a longer-term pattern, |
2:19.0 | etc., all of which have the same shape. And in fact, the basic, the underlying pattern is |
2:25.1 | what we call a zigzag, which is merely the price goes up, the price goes down, and then the |
2:29.5 | price goes up again. Or there's one in the opposite direction, of course course and you can then put these zigzags together |
... |
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