Our goal is to develop decision making innovations that improve performance in AI-enabled investment vehicles by harnessing the power of the human-computer collaboration.

Ergo, we view investing as a shared decision making exercise whose participants contribute idiosyncratic knowledge and expertise.


 

Multiple Moving Parts

There is little debate that aspects of trading such as speed of execution and stock picking are best left to machine algorithms.  To outperform an alpha engine in a high-performance AI-powered algorithm requires decisive human control and consistent application of an explicit market strategy.

Within financial markets, information asymmetry drives competitive edge. We employ a minimum variance strategy, relying on forward-looking information from options markets.


Today’s active investors are like the centaur of Greek mythology — half human and half horse — running with the rapid feet of data-driven technology, yet carrying the same tempestuous human heart. It is implausible to regard emotion as a dismissible part of investment decision-making since managing risk is replete with ambiguity and uncertainty. And uncertainty is inherently aversive.

Buy-sell decisions essentially reflect the cognitive ability of investors to make rational decisions about timing and position size. But such decisions are multifaceted, requiring integration of algorithmic trade signals and risk-reward calculations while continuously self-regulating emotions and cognition.

Taken together, one’s ability to succeed in this complex environment relies upon three things: (1) good AI, (2) quantitative decision support tools, and (3) keen attentional skills and self-awareness.

Please join us for one of our upcoming retreats.  We’ll tell you all about how to trade like a centaur!