From Benchmark to Reality

How to Define a Fair Year-End Performance Expectation for Your Investment Advisor

In the previous article, we discussed how to build fair benchmarks and adjust for currency and inflation. That framework is essential for long-term analysis.

This article takes a different perspective. Instead of asking what should happen over decades, we ask a simpler question:

At the end of a specific year, how can I objectively evaluate whether my investment advisor delivered what was reasonable given market conditions?

This approach has one major advantage: At year end, the facts are known.

• Asset class returns are known.
• Sector returns are known.
• Currency movements are known.
• ETF proxies are observable and investable.

The following approach outlines the steps required to evaluate the performance:

Step 1. Define the Portfolio Structure & Constraints map

Before we look at any returns, we need to translate the mandate into clear, testable constraints. These constraints define what the advisor was allowed to do and, by extension, what a “fair” comparison should look like. 

Base currency (e.g. CHF). This is the reference currency for reporting and evaluation. In practice, it is the currency the investor ultimately cares about. It also determines how we treat foreign holdings: even if an ETF is priced in USD or EUR, performance must be interpreted through a CHF lens (either via actual FX moves or via hedged share classes, depending on what the mandate permits). 

Other key constraints typically embedded in a mandate

• Asset-class limits: minimum/maximum allocations to equities, bonds, real estate, and alternatives.
• Geographic limits: where equity exposure may come from (e.g., US, Europe, Switzerland) and whether home bias is required or capped.
• Sector tilts (if explicitly permitted): e.g., “US tech tilt” or “global healthcare tilt” should be treated as intentional, measurable deviations from a broad equity sleeve, not as incidental outcomes.
• Implementation constraints: whether exposures must be unhedged/hedged, use of ETFs vs active funds, liquidity limits, concentration limits etc.

With that framing, the example mandate can be written as a constraint map:

• Base currency: CHF
• Equities: 60% total
  • 20% World equities
  • 20% US equities core
  • 5% US (tech tilt)
  • 10% Europe
  • 5 % Emerging markets

• Bonds:
  • 25% Global bonds CHF hedged
  • 10% Corporate bonds Switzerland
• Cash: 5%
• Real estate: zero
• Alternatives: zero
• Currency exposure: 45% USD, 40% CHF, 10% EUR, 5% other currencies
• Hedging of selected currencies: i.e. USD 

Step 2. Choose Transparent ETF Proxies

Why we use proxies, and what they are

A mandate describes desired exposures (e.g., 60% equities with a US tech tilt), but it rarely specifies the exact instruments, managers, or trading path used to implement those exposures. To evaluate performance fairly, we therefore build proxies: transparent, investable reference instruments (typically ETFs) that approximate each mandated sleeve as closely as possible.

The purpose of proxies is not to “pick the best ETF,” but to create a replicable baseline for measurement. This baseline helps us answer: How should the portfolio have behaved if it had implemented the mandate in a straightforward, low-friction way? In other words, proxies translate constraints and tilts into observable total returns that can be combined into a mandate-consistent reference portfolio.

Using ETFs as proxies is practical because they are investable, their total return is observable and they help avoid index-only distortions that can arise when relying on theoretical indices that ignore real-world costs.

With the proxies defined, we can now construct the reference mandate portfolio by combining the chosen ETF returns according to the target weights (and applying the correct CHF treatment, including any hedging rules). 

Please find below a table of alternative proxy options, depending on your investment preferences:

Step 3. Compute Proxy Returns and Translate Them into CHF

Once the proxy set is fixed, the next task is simply to observe what each proxy delivered over the year and express those results in the mandate’s base currency (CHF). We start from each ETF’s local-currency total return, because that is what the instrument actually delivered in its home market. We then translate foreign sleeves into CHF using the realized FX move over the same period, so that the proxy portfolio reflects the return experience of a CHF-based investor.

CHF return = (1 + local return) × (1 + FX change) − 1 

The 2025 picture illustrates why this matters. Some sleeves look similar in local and CHF terms: Europe equities stayed broadly intact, and CHF corporate bonds are effectively unchanged because the exposure is already in CHF (low single digits in both). By contrast, USD-heavy equity sleeves show that FX can dominate the CHF outcome: a US tech tilt that was very strong in local terms ends up much more muted in CHF (single digits), and even US core equities compress from a high-teens local return to only a low single-digit CHF result. The most striking example is World developed: positive in local terms but negative once expressed in CHF, highlighting how translation can flip the sign of performance in a CHF-based mandate.

As a helpful sense-check on the FX effect in 2025: both EUR and USD weakened versus CHF over the year. Measured on the EUR/CHF exchange rate, the euro depreciated by just under 1% against the Swiss franc in 2025, while the USD/CHF exchange rate shows the US dollar depreciated by roughly 12.5% against CHF over the same period. 

Please note that mechanically, there is no modelling involved: for foreign exposures we apply the actual FX translation over the year (equivalently, compounding local return with the currency move) to obtain the CHF return. This is the return that belongs in the mandate benchmark, because it is the one the investor actually experiences in CHF.

Step 4. Evaluate portfolio performance

With the proxies expressed in CHF, the final step is to put the mandate back together: we apply the mandate weights to each proxy sleeve and aggregate them into a single, portfolio-level return. 

The result is a CHF-denominated “achievable” outcome for the year: what an investor could reasonably have earned by implementing the mandate through liquid, low-cost ETFs, including the same regional mix, the same permitted tilts, and the same FX reality. That’s the key win: we now have a benchmark that is practical, transparent, and aligned with the rules of the mandate, rather than an abstract index blend.

From here, performance evaluation becomes straightforward. If the manager lands broadly in line with this proxy portfolio, they essentially delivered what a passive implementation would have delivered. If they exceed it, they likely added value through security selection, timing, or more efficient implementation. If they fall short, the shortfall is meaningful, because it is measured against accessible alternatives that respect the same constraints.

Step 5. Adjust for Inflation

Once you have the portfolio’s nominal return in CHF, you can add one final lens: what happened to purchasing power. In Switzerland, inflation in 2025 was very low (around +0.2% on average for the year), so the gap between nominal and real performance is typically small, but it is still a useful sense-check when you want to express results in real terms.

A simple way to do this is to convert nominal into real terms:

Real return = (1 + nominal CHF return) / (1 + Swiss inflation) − 1

This complements the assessment by showing whether the outcome also improved purchasing power, not only the portfolio’s value in nominal CHF.

Conclusion

Year-end performance reviews can easily become emotional. One year the narrative is that markets were “uninvestable,” the next that returns were “obvious in hindsight.” Sector rotations get labelled unpredictable, timing decisions get defended or regretted, and the discussion drifts away from what actually matters: what the mandate allowed, and what was achievable within those rules.

A proxy-based approach brings the conversation back to solid ground. By translating the mandate into transparent, investable ETF sleeves, combining them with mandate-consistent weights, and expressing outcomes in CHF including actual FX movements, you replace storytelling with a reference point that is observable and repeatable. The numbers already exist - the presented framework simply organizes them into a fair comparison.

This discipline removes three recurring distortions: blaming the manager for market declines that would have hit any mandate-consistent portfolio, crediting the manager for broad market rallies that a passive implementation would also have captured, and overlooking currency effects, which can materially change the CHF outcome even when local performance looks strong.

Just as importantly, it forces clarity. If the mandate allows sector overweights, those decisions must be measured against the relevant sector proxies, not against broad market exposure. If the mandate embeds home bias, it must be reflected and assessed through explicit Swiss allocation. In other words: allowed tilts should be benchmarked as intentional choices, not treated as accidental alpha or unexplained risk.

There are limitations though: ETF proxies are approximations, not perfect mirrors of every implementation. Transaction costs, rebalancing frictions, and asset management fees can shift realized outcomes. The right response is not to abandon the method, but to improve it in the next iteration by systematically adding these effects where material.