Jon Stojan
Image credit: Ridge Capital Solutitons
When Luc Longmire, Kayla Van Boven and Adam LoPorto set out to build passively managed Equity Advisor (“algo”) based portfolios for themselves, they had no idea where their journey would take them.
The trio met years back, learning and growing together as retail traders. As their trading experience grew, so did their desire to diversify their accounts and position themselves to more passively manage positions. As any successful trader will admit, successful trading is not the one-hour-a-day drill the online social-media gurus are selling: it’s a time consuming and often nerve-wracking exercise in research, grit, mental fortitude, and maybe a bit of luck.
Ray Dalio pioneered the idea that computers make better financial decisions than people, because computers don’t act on emotion, greed, or skewed perceptions of the world around them. On the back of that investment and idea, Dalio built Bridgewater – the world’s largest hedge fund.Computers make decisions based solely on cold-hard data. Humans, on the other hand, are subject to lapses of judgement, distorting information to fit a narrative, fatigue, confusion, greed, and the account-crushing “Fear of Missing Out.” Longmire, Van Boven and LoPorto wanted to harness that power for themselves and to service a collective of family offices in their personal networks.
After hiring several developers, many of whom either failed in their task or disappeared with the trio’s money, they were left with several algorithmic systems that worked well. But they still lacked one important feature…
Equity Advisors (often called “Algos” or “Bots”) have an inherent fatal flaw: they utilize a single strategy, trading on a fixed set of rules. One strategy may work well and have a positiverisk/reward ratio in one market structure, but when the market shifts the risk/reward profile of the strategy can change dramatically, overexposing an account to risk.
Being the relentless geeks they are, the trio wanted to harness the power of Artificial Intelligenceand Machine Learning to not only select and automatically apply strategies based on historical data, but build new strategies as the market evolved.
But there was one problem: Longmire, Van Boven, LoPorto and the third-party development team that had built their previous algorithmic systems knew nothing about Artificial Intelligence. So, the trio hit the streets to find an A.I. developer with experience in the financial markets.
After much searching, the trio struck digital gold… they were introduced to a small collaborative team, including an MIT educated software engineer with NASA-level credentials, finance professionals and programmers. The team had already developed a base-Ai system that was designed to constantly monitor 150,000+ data points across 30 markets, extract strategies from that data, rank them according to risk/reward profiles like Sortino and Calmar ratios, and then propose open trade portfolios to seek above-average returns with controlled risk. Marketed almost exclusively to institutions, Longmire, Van Boven and LoPorto proposed to offer derivatives of these systems to retail traders, family offices and small funds.
After striking a partnership with the development team, the trio launched Ridge Capital Solutions in the United States, offering an initial three fully Ai/Machine learning based systems (R-10, R-50 and R-400), later adding a fourth FOREX offering (R-X25), and R-C100, a crypto-currency pair trading system. Each system applies a range of “sub-systems” – numbering from 8 to 31 depending on product – which each utilize independent strategies calculated and back tested to be as minimally cross-correlated as possible. What used to require dozens of analysts and traders can now be done using Machine Learning cores pushing strategies out to each independent sub-system. As the market evolves, so do the strategies the systems employ.
With over 70% of all intraday trading at the institutional level originating with computers as operators, Ridge Capital Solutions is poised to bring that power to retail traders and family offices, all with no performance fees.