The Minotaur Global Opportunities Fund was flat (+0.03%) in February, outperforming the MSCI ACWI (Net, AUD) which fell 0.4%. This marks the third consecutive month of outperformance in a flat-to-down tape. We take some comfort from that because capital preservation and lower drawdowns than the market are explicit design goals of the strategy - and the portfolio has behaved that way through a choppier start to the year.

Two things sit behind that outcome: (1) vigilance i.e. a willingness to respond as the world (and therefore risk) changes, and (2) diversification across geographies, sectors, factor exposures and market caps, so the fund is never a single bet.

Prices move, so we move

A point we often make internally is simple: the right portfolio is the one that best reflects the world today at the prices today. In January, our view of risk changed meaningfully, and we reduced exposure accordingly, ending the month with a 68.5% net exposure, our lowest since inception.

In February, prices moved just as quickly as the narrative, particularly in software, where several names fell more than 40% in short order. Markets have a habit of overshooting, and when they do, the risk/reward can change dramatically. We used that drawdown to cover shorts and selectively rotate back into positions where the asymmetry improved.

It’s worth emphasising the nuance here. We still think software is facing genuine uncertainty as AI reshapes workflow, pricing power, and moats. But in a sector where sentiment can swing from euphoria to fatalism in weeks, helped by the odd AI Doomsday report, our job is to stay dynamic: cut risk when the set-up deteriorates, and lean back in when the market offers it back at meaningfully better prices.

Staying diversified while volatility creates openings

Software has been the most topical arena for repositioning, but it is only one slice of the overall portfolio. Our capital-protection mindset comes from ensuring we’re diversified across multiple independent return streams so that even when one pocket of the market is violently repriced, the fund is not hostage to a single outcome.

That diversification helped in February. Our commodities allocation was additive, with a number of positions up strongly over the month. We also continued to harvest gains where the market repriced faster than fundamentals. The best example was Lumentum, which rose substantially over the three months we held it; as the upside compressed and the set-up became less attractive, we exited and recycled capital into better risk/reward opportunities.

What didn’t work

Even with a more defensive stance, it was hard to avoid idiosyncratic drawdowns during reporting season. We saw disappointing earnings reactions in Rheinmetall and First Solar. In both cases, we trimmed and took profits. Both have been meaningful contributors since inception and we remain focused on protecting the gains we’ve earned rather than round-tripping them. Wizz Air was also a detractor after a discounted secondary late in the month. Overall, the number of positions that were down was broadly similar to those that were up reinforcing that February was less about a roaring tailwind and more about portfolio construction, risk control, and active decision-making.

Translating stories into numbers

Investing is a creative activity. You need to picture a future that doesn’t exist yet, work out how a company’s market evolves, what goes its way, what doesn’t, and then figure out what that future is worth. But creativity without rigour produces loose, risky portfolios. The real skill is taking a qualitative view and translating it into hard numbers to test whether the story actually supports the price.

That’s what financial modelling is really about, and it’s one of the most interesting parts of investing. Take Pearl Abyss, a Korean game developer we own that’s launching Crimson Desert in the coming weeks. There’s no point building a generic earnings model for a company like this. What matters is how well the game sells. So we model it across five scenarios, each anchored to a comparable game launch. These range from a niche outcome like Dragon’s Dogma 2 (well-reviewed but faded quickly) to global hits like Monster Hunter World (which extended its life through expansions). Each scenario produces a different revenue path, a different valuation, and we assign probabilities to each. The model becomes a structured way to debate what we actually believe and what the evidence supports. With the launch now weeks away and early signals encouraging – over three million Steam wishlists, strong tech previews, and review codes sent unusually early – we’ll soon find out which scenario plays out.

Historically, though, the interesting part of modelling (structuring around what matters, painting the scenarios, debating assumptions) is only a fraction of the work. Most of the time goes into mechanics: formatting, linking cells, populating line items, checking that everything ties. It’s necessary but low-value, and it’s been one of our key bottlenecks in getting through more companies at the depth we want.

This month we added financial modelling as a core capability in Taurient, and it directly addresses that bottleneck. The mechanics are now largely automated, so we spend our time on the decisions that actually drive returns. What makes it more robust than models we’ve built previously in our careers is the documentation that comes with it: every model is accompanied by a methodology note explaining how we’re modelling the business and why, alongside a structured assumptions file where each input has a written rationale. In traditional modelling, a lot of that thinking lives in an analyst’s head. Here, it’s explicit, which means we can debate the structure, drill into individual assumptions, and go back to any point in time to understand what we believed and why. The higher-level decisions about what matters for a company still rest with us; the technology lets us stretch further.

Preservation requires learning from the good and the bad

The last three months have reinforced our belief that a relentless focus on risk combined with the ability to act decisively as conditions change can deliver a smoother ride, without sacrificing upside. We’ve been able to hone these skills from years of learning including running concentrated factor and sector-bet portfolios in former lives. That experience proved instrumental in teaching us (the hard way) and how we got to the diversification thinking you see today.

As Diogenes said: “As a matter of self-preservation, a man needs good friends or ardent enemies, [or good or ardently bad investment calls] for the former instruct him and the latter take him to task.”