Common Questions

Hedge funds have largely disappointed investors over the recent cycle because of their poor performance. Many institutions have shifted their alternative allocations to venture capital. Our experience suggests that we can swim against that trend by offering qualified investors a robust product with fully-validated performance metrics.

The massive shift to index strategies, in part because of investor frustration with actively-managed approaches, has bifurcated the investment industry. Our strategy amplifies index positions without materially-greater fees. In a sense, our core fund is an alternate window on a US equity holding.

The post-pandemic environment is the ideal context for a new investment product. We believe that investors are now treating the S&P 500 as a near-cash holding because of its role as a beacon for retirement assets. We, in turn, can add real value to that portfolio bias via a different risk-return profile.

AI has almost become jargon. But we reckon that we were developing our trading models well before Silicon Valley distorted the use of the term for their own venture purposes. Granted, we are a young firm, but any firm in this space is young by definition. Some asset-management firms have adopted AI phraseology to explain trading activity in traditional funds; we infuse it into our primary strategy.

We do not use “big data,” at least in the conventional sense. There are massive problems with the integrity of so-called alternative data sets, their internal consistency over time, and the ability to sustain those data sets in part because of regulation. Our approach is “derived data.”

Our data is proprietary, extracted from an AI-driven analytics system based on price movement in the E-mini S&P500 futures contact. Our algorithms seek to separate statistically-significant, tradeable signals from noise. Importantly, we layer this data to ensure multi-dimensional interpretation.

Generating bespoke derived data has two clear advantages, firstly it gives our firm data independence and secondly it helps avoid the rabbit holes of data complexity (we know why we are deriving the data we use). The strength of our approach is validated by seven years of development, testing, and calibrating. By comparison, we cannot identify a single “big data” set with that sort of pedigree.

The headline story is quite streamlined: We manage an AI-based trading strategy that exploits behavior in an underlying index fund. At this time, our approach is limited to US equities, but our firm’s strategic evolution calls for multiple index-related products worldwide.

Some asset managers have been successful with tweaking index structures to eke out incremental gains beyond what the underlying index would have delivered. Our approach turbo-charges that concept by using a different way of exploiting information and understanding inefficiencies, not in seeking to capture market inefficiencies. Through the application of AI, we often have done much better than adding 20-or-40 basis points in any discrete period.

Because our strategy is based on futures trading, we do not have the same sort of capacity constraints that an active manager could have. We are, however, taking a measured approached to uploading new clients as we scale the product. We want to calibrate our relationship management activities effectively with those institutions who have made early commitments.

The Northern Ireland-based holding structure traces its heritage to 2013. Plotinus Asset Management, the regulated Cayman Islands entity, is much younger; it was authorized in 2019. The core research and development efforts have evolved over many years. We set up the asset-management entity in tandem with our move to directly commercialize our data analytics.

Traditionally, new-to-market fund management companies are narrow partnerships because of the volume of capital required to launch a firm. In our case, the Northern Ireland company, where our data analytics are maintained, has benefited from outside capital contributed by government-backed Invest Northern Ireland and the EU-sponsored European Regional Development Fund. Minority stakes are held by UK citizens.

Plotinus Ltd. is headquartered in Northern Ireland, but our core fund is regulated in the Cayman Islands, where selected service providers to the fund are also based. Plotinus Asset Management, the advisor to the fund, is regulated by both the Cayman Island Monetary Authority and the US National Futures Association. Some aspects of our on-the-ground responsibilities in the United States and elsewhere are handled by a Miami-based consultancy.

We have assembled a team of world-class service providers to ensure that we meet best-in-class standards in the asset management industry. Our own process in identifying these names was designed to find solicitors, administrators, and consultants who both excel independently and embrace entrepreneurial clients. We have balanced reputation and skill, rather than just mindlessly retaining marquee names.

For the fund, leadership is now composed of two senior executives at Plotinus and one external director. We work closely with advisors that span the industry, so as the core product grows in stature, we will benefit from pre-defined arrangements with industry mentors to join our fund board.

Plotinus is set-up as an institutional asset manager for those investors overseeing offshore pools of capital. We do not have an internal capability to market to retail investors across jurisdictions. However, we welcome investments from quasi-institutions such as family offices and ultra high-net-worth names, where permissible under regulation.

We are positioning the fund as a new window for investing in the US stock market. Accordingly, based on historical data, our risk-return profile is better than investors would have seen through a traditional index fund. We cannot always guarantee that outcome.

Strictly speaking, the Cayman fund was launched at the beginning of the fourth quarter 2020. The fund strategy, however, is based on our work as a CTA, which reaches back to June 2018. Since inception in June 2018, our work indicates that investors would have outperformed the S&P 500 on a risk-adjusted basis over the reach of that three-year period. Additional information is available.

We were actively managing the strategy during the fourth quarter of 2018 and the first quarter of 2020, when we saw extreme drawdowns in the S&P 500. During both periods, we were able to protect investors against the full brunt of the sell-off. As expected, the AI-based overlay helped to mitigate this volatility. Past performance is not an indicator of future results.