The idea back in 2010 to launch a platform that would cover the Nordic hedge fund space came hand ind hand with another aspiration. Very early on, it stood out: creating an award to identify and celebrate “the best” funds and managers in the region. But how to go about it?

Looking at existing industry awards helped, but inspiration also came from outside finance. In Formula 1, the winner earns disproportionately more popints than the runner-up. In judged sports like ski jumping or figure skating, the highest and lowest scores are discarded to reduce bias. The Oscars rely on peer voting, adding a layer of subjective judgment. Across all of them, there is a structure that people intuitively understand, even if they do not always agree with the outcome. We even drew some input from Eurovison!

At the same time, there were approaches I found less compelling. Purely objective measures, like the stopwatch, are clean and absolute, but rarely tell the full story. Translating that into our world, simply declaring the highest return as the winner felt equally incomplete.

So we set out to build something that was structured enough to identify “the best,” yet nuanced enough to reflect the complexity behind performance.

Performance was the obvious starting point, but as a stand-alone it was quickly dismissed. A simple “best return wins” framework ignores risk and other key metrics entirely. Moving to risk-adjusted measures, such as the Sharpe Ratio, improved things, but only to a point. The more we explored it, the clearer it became that no single metric would capture what makes a fund truly stand out.

The challenge was on! Should higher returns be rewarded more than consistency, or should a smoother return profile carry greater weight? How should drawdowns be treated relative to volatility? What about skewness, or correlation to broader markets? Over what time horizon should any of this be measured? Are they equally important and telling, or do they need weighting? Each parameter seemed reasonable in isolation, but the moment you combined them, you were making choices. And each of those choices implied a bias.

It also became obvious that comparability is not a given. Evaluating funds with very different strategies, volatility targets or objectives against each other can feel like comparing a NASCAR lap time to that of a racehorse, on a different track, under different conditions. Both may be exceptional, but the framework determines how that excellence is measured.

Even the market environment plays a role. In years when beta lifts most strategies, strong performance becomes less informative. But should that be stripped out entirely, or is navigating those conditions part of what defines a good manager?

What became clear was that it was no longer about finding the perfect metrics, but about constructing a set of rules that could combine and weigh multiple indicators in a consistent and transparent way.

From the outset, I was convinced that whatever we built had to be fair, repeatable and objective. Just as importantly, it had to be credible. As a small, unknown platform at the time, we did not have that credibility ourselves.

We turned to the Stockholm School of Economics and the Swedish House of Finance. What started as rough ideas and analogies gradually evolved, through discussion and academic input, into a structured framework. Students from KTH Royal Institute of Technology under supervison later implemented and coded the model, translating theory into a tool that would run the calculations autonomously.

The result is a rules-based quantitative ranking that evaluates funds across multiple dimensions, including performance, volatility, skewness and risk-adjusted returns, both on a standalone basis and relative to comparable peers and the broader Nordic hedge fund universe. In simple terms, we established a way of measuring the “lap time” of each manager under comparable conditions, and made those rules transparent for everyone to see.

We had the academic, theoretical angle covered. What was still missing, however, was the real world value of this outcome and some human element. Numbers can tell you what happened, but they rarely capture the full context. Allocators form views through experience, interaction and judgment, often based on factors that are difficult to quantify. To reflect that reality, we introduced a qualitative layer through a jury of experienced asset allocators.

The composition of this group is deliberate. Members come from different institutions, countries and backgrounds, ensuring a diversity of perspectives and reducing the risk of a single dominant view. Their independence is a critical part of the process, not an afterthought, and an important contributor to the credibility of the outcome.

The jury evaluates the highest-ranked funds from the quantitative model at their full discretion. To maintain balance, scores are normalized, and extreme observations are removed by discarding the highest and lowest inputs for each fund, in line with practices from judged sports designed to limit bias.

This produces a second, qualitative score. The final result is a simple combination: 50 percent quantitative, 50 percent qualitative. Together, they determine the three funds on the podium.

We believe this is a fair and transparent approach, one that runs without interference and produces a clear outcome based on predefined rules.

Those rules are not designed to reward any single metric in isolation, which is why it may happen that a fund with a higher Sharpe Ratio or lower drawdowns, or even “did better across the board” does not end up on the top step. Taken individually, those arguments are often right. Taken together, within the framework, they are not decisive.

The simple fact is, yes, if the rules were different, it may likely change the result.

That is true in sports as well. In football, the winner is determined by who scores more goals by the final whistle. If instead you measured distance covered, passes completed or fouls avoided, or combines these factors in some way, the result might look very different. Even when the rules are the same, outcomes depend on how they are applied, interpreted and weighted (headballs count double). Anyone who has watched a Sunday little league match where the coach of the home team or some random parent also acts as referee will have seen how interpretation if the ball was in or out, offsdide or not, alone can shape the result within the same framework. Rules need to be objective, and not subject to interpretation.

Having the perfect model may have been the naïve ambition, but that ideal model does not exist.

The framework for the Nordic Hedge Award is transparent, consistent over time and credible, where the outcome follows logically from the rules that define it. As likely everything in life, change the rules and you will change the result.

Picture: (c) Conny Schneider-unsplash.com