With summer officially over and the sailboat now hoisted out of the water, it’s a bittersweet moment. On one hand, we have our time back, fully focused on the tasks ahead. Yet, by the time spring returns, we know we’ll miss those warm days on the water. As we shift into autumn, I’ve taken a moment to reflect on our strategies and where we’re headed.

Gamma Goblin’s Steady Outperformance

Our Gamma Goblin strategy continues to deliver steady, reliable returns. In September, it posted a 0.5% gain, while the QQQ achieved 2.6%. Despite the QQQ’s stronger recent performance, since Gamma Goblin’s inception, it remains ahead of its benchmark by 2.5%. This consistent outperformance reinforces our confidence in the strategy’s ability to deliver over the long term.

The information ratio for Gamma Goblin stands at 1.21, significantly ahead of the benchmark’s 0.63%. Gamma Goblin, in many ways, has been running a marathon—a slow and steady pace, while the competition occasionally surges ahead. But just as in calculus, where the slope of the curve may change at various points, it’s the area under the curve that matters. The QQQ may have had a steeper slope this month, but the cumulative advantage we’ve built with Gamma Goblin has ensured we stay ahead, a position we intend to maintain.

What’s particularly notable is that we’re only 40% invested in the market on average, with 60% in cash generating returns of its own. We don’t include these cash returns in our performance reporting, since if they were to make or break our results, it would be all for naught. To calculate the Sharpe ratio, one would subtract the risk-free rate, but this cash information allows readers to estimate it themselves. With proprietary capital in play, our focus remains firmly on generating profits. Although we keep our reporting straightforward, transparency is key, and we will continue to clearly communicate our progress.

R&D Update: Tackling the Hard and Easy Problems

On the research front, we’ve been focusing on some hard questions in both finance and broader scientific endeavours. AI developments, particularly the latest from OpenAI, have prompted us to re-evaluate how we approach these challenges. A particularly compelling article that has shaped our thinking is “Artificial Intelligence for Science: The Easy and Hard Problems” (link to article).

We’re committed to tackling the hard problems ourselves, while acknowledging that automation and AI will increasingly handle the easier tasks. This aligns well with Steve Jobs’ “100x theory”—the idea that the right tools can multiply an individual’s productivity exponentially. We believe that these AI-driven tools will only enhance our research capabilities moving forward.

In our R&D efforts, we are focusing on three main areas: refining our asset allocation quant strategies, optimising intra-market option arbitrage, and exploring an advanced version of Gamma Goblin that estimates predictable convexity in a new, more efficient way. These three areas form the backbone of our ongoing work, and we are confident that they will position us to remain at the forefront of strategy development.

Sage: Reflecting on the Setback

September posed a challenge for our Sage strategy. Despite efforts to recalibrate by cutting capital and tripling the number of positions, Sage unfortunately posted a loss of -1.8%, while its benchmarks—GVIP and SPY—rose by 4.5% and 2.9%, respectively. It’s important to note that Sage is a strategy we have invested in, but it was not developed in-house. We’re working closely with the strategy’s manager to help improve its performance and ensure it aligns with our broader objectives.

That said, setbacks like these are part of the process. We will reduce the allocation further and continue to refine the approach. There’s no shame in reflecting on what didn’t work—indeed, this is often where the most valuable insights come from. We’re even considering adding an RIP section to the website, not to bury strategies but to document them for future analysis. The information gleaned from these experiences is immensely valuable and can inform future innovation.

Looking Ahead

We remain as committed as ever to the work we are doing. Even when certain strategies face difficulties, the lessons learned only enhance our ability to build stronger, more effective approaches in the future. As always, we’ll continue to pursue these efforts with care and precision.

In the spirit of automation, which we embrace fully, I must add that this newsletter was produced with the assistance of a large language model (LLM). It’s a fitting example of how we aim to streamline our processes wherever possible, allowing us to focus on the tasks that truly move the needle.