Social Mood Conference  |  Socionomics Foundation

Developer, programmer and entrepreneur spoke at 5th Annual Social Mood Conference

ElliottP_2Elliott Prechter’s fascination with technology led him to attend MIT in 2002 and ultimately to join Microsoft in 2006. His interest in financial markets intensified during the 2008 crash, and he left Seattle in early 2011 to help start an algorithmic hedge fund in Las Vegas. In late 2012, he joined Elliott Wave International to develop EWAVES, an artificial intelligence technology that automates Elliott wave analysis. He recently spun the project off into a separate company, Qualitative Analytics. The firm’s technology powers Flash, a subscription service that provides real-time buy and sell alerts as opportunities arise in futures and equities markets.

On April 11, Elliott joined a diverse roster of expert speakers at the 2015 Social Mood Conference in Atlanta. Before the conference, Elliott spoke with us about the event, his lifelong interest in technology and some of the latest developments with EWAVES.

Socionomics Foundation: Can you talk about your background and how it shapes your work on EWAVES?

Elliott Prechter: My education at MIT provided me with a theoretical background in hardware and software, and my work at Microsoft exposed me to the practical world of building large projects. Our EWAVES repository is nearing 200,000 lines of code for a team of three developers. Maintaining this repository would not be possible without documentation, design effort, constant re-factoring and, most importantly, extensive test coverage.

SF: Were you always passionate about computers?

Elliott Prechter: For as long as I can remember, I wanted to work with technology. I think my first major obsession in this area was in 3D graphics, which require “pedal-to-the-metal” performance. In fact, it was probably this early fascination with high-octane performance that led me to a design for EWAVES 2 that leverages modern machines far beyond that of EWAVES 1. It has better algorithms, cache-awareness and concurrency. The significantly faster analysis process in EWAVES 2 is allowing us, for the first time, to do the rapid research required to iteratively improve the program.

SF: EWAVES uses the Elliott Wave Principle—and only the Elliott Wave Principle—to generate its analysis. What attracted you to this approach?

Elliott Prechter: It’s clear to me that Elliott waves are the only truly robust methodology for financial analysis. All other approaches to market forecasting I have studied either don’t work or are transient and eventually burn out. Additionally, as an engineer, I am naturally attracted to solutions with theoretical elegance.

SF: Your work has a thorough research side in addition to its practical side. Would you say a few words about each?

Elliott Prechter: Sure, let’s start with the research side. EWAVES distils Elliott wave analysis into a definite and reproducible function, allowing our implementation of the Elliott Wave Principle to be formally researched. This should lead to new discoveries and ultimately better products and services from our firm, Qualitative Analytics. We also hope that our software will eventually help the Socionomics Foundation to publish academic papers that further validate the Wave Principle and socionomic theory. The EWAVES project, however, will never be “done.” There is always room for improvement.

On the practical side, we offer a variety of services for people interested in capitalizing on the real-time opportunities that we identify in the markets. Readers can learn more and explore our open-access publication at ewaves.com.

SF: How does your work relate to social mood?

Elliott Prechter: Social mood is patterned according to the Elliott Wave Principle, and these patterns manifest in financial price data. EWAVES analyzes financial price data through the lens of the Elliott Wave Principle to forecast the future. Its approach is in line with the Socionomic Theory of Finance. It eschews economic “fundamentals” and recognizes that since social mood is both patterned and endogenously regulated, then the best way to forecast it is by looking at the patterns in a good sociometer.

SF: You attended the 2014 Social Mood Conference. Can you tell us about the experience?

Elliott Prechter: Last year was a lot of fun! My favorite presentation was Matt Lampert’s talk about the Las Vegas real estate collapse. It still amazes me how most people always apply linear projection in their analysis despite the fact that it always results in devastating overleveraging right at the most inopportune times.

SF: Now you’re returning to the conference as a speaker. What excites you the most?

Elliott Prechter: I’m looking forward to speaking in front of a group, which I greatly enjoy—especially if the topic is something I am passionate about. The EWAVES team has been hard at work for a long time, and it’s rewarding to finally be able to discuss some of our efforts in person. I am also especially looking forward to Alan Hall’s “Deep Time” presentation—the socionomic perspective on the evolution of the universe, the solar system, earth, life forms and human culture. It should yield some new insights.

SF: Thank you, Elliott.

Watch Elliott Prechter and the ten other excellent presentations from the 2015 Social Mood Conference right now from your PC or mobile device via an on-demand broadcast>>