Stephen Simmons, Founder & CEO
Since the publication of Ralph Nelson Elliott’s “The Wave Principle” in 1938, traders have been vexed by the complexity inherent in the techniques used to identify Elliott Wave patterns. This is largely owed to the fractal nature of the interrelated patterns, which can give rise to vast pattern combinations. These cyclic patterns are bound to specific phases of crowd psychology, and a thorough analysis of them could take hours on any given price chart. Being well-versed in trading system concepts and implementation, as well as designing novel computational approaches, Stephen Simmons points to the time and tedium typically involved in effectively applying Elliott Wave analysis consistent with the mathematical rules which govern the constituent patterns. Traders also often identify multiple valid wave ‘counts’, each with associated probabilities. These counts are commonly assessed using external indicators or measurements that complement the core Elliott Wave specifications. “Even after so many years, no one has successfully delivered a comprehensive automated Elliott Wave analysis platform that is accessible to a wide audience,” he says. Inspired by a vision to enormously accelerate the process and elevate the accessibility of Elliott Wave trading, Simmons laid the cornerstone for WaveBasis.
At the helm of WaveBasis as the Founder & CEO, Simmons leads his team to fulfill the company’s mission of advancing the science of Elliott wave pattern detection and analysis with a unique array of specialized tools and algorithms. WaveBasis’ powerful and intuitive tool suite, backed by a sophisticated computational engine, empowers traders to seamlessly assess wave counts at multiple time frames and quickly validate trade theses based on consistently valid Elliott Wave patterns.
Born from a singularly robust dataset based on Elliott Wave reasoning, WaveBasis enables traders to effortlessly detect patterns and backtest Elliott Wave systematic trading methodologies
The company is also tackling one of the ever-present hurdles in the Elliott Wave space—backtesting, which demands computationally intensive scrutiny of massive amounts of historical market data. Borne from a singularly robust data set based on Elliott Wave reasoning, WaveBasis enables traders to effortlessly detect patterns and backtest Elliott Wave systematic trading methodologies. “We’re committed to objectifying, simplifying, and accelerating Elliott Wave analysis for traders, as well as providing the crucial raw inputs for algorithmic trading,” states Simmons.
From seasoned traders and technicians having experienced the hardships of manual Elliott Wave analysis, to novice traders looking to integrate Elliott Waves into their arsenals, WaveBasis caters its solutions to them all. The company’s platform also comes equipped with educational tools to help get newer traders up to speed on Elliott Wave concepts. Recently, one of WaveBasis’ clients, an individual trader and an intermediate-level Elliott Wave analyst, complimented the platform for being ‘beautifully designed and intuitive’. The trader found benefit in the highly interactive tools, commenting that his trading profits and his confidence in applying Elliott Wave principles had been boosted in a surprisingly short time. “A key thread that runs through our UI/UX design process is our aim to anticipate effective trading workflows and to automate common tasks in a way that is efficient and intuitive,” Simmons adds.
With similar case studies highlighting the company’s early impact, Simmons envisions a bright future which includes trading advisory services built upon its existing high technology foundations. That being said, WaveBasis is currently working toward publicly unveiling innovative strategy backtesting tools on the existing platform. “On the immediate horizon, we’re looking forward to continuing to enhance the platform with exciting new capabilities that allow individual traders and other market participants to harness the full potential of Elliott Wave analysis,” concludes Simmons.