Building Benchmarks for Alternative Investments Using Model Portfolios

22 June 2025 | 
Dmitri Alexeev
Sample Model Portfolio. Source: AlphaBot
The Benchmarking Problem in Alternatives

Alternative investments — including private equity, hedge funds, infrastructure, and real assets — offer diversification and potential outperformance. But unlike traditional asset classes, they don’t fit neatly into well-known market indices.

How do you benchmark a private equity fund? Or a real asset portfolio? Unlike equities (S&P 500) or bonds (Bloomberg Agg), there’s no standard reference for many alternatives. 

There are many sophisticated quant tools for performance analysis, including Factor Analysis, Regression and Time-Series Modeling, PCA (Principal Component Analysis), growing more and more popular Machine Learning Methods such as Clustering, and Simulation and Bootstrapping. However, their sophistication is often negated by the limitations of the data available for alternative investments – from frequency of returns (quarterly or even annual for private equity, RE holdings, etc) to different kinds of biases present in databases of hedge fund returns (such as survivorship and backfill biases). Applying complex analysis tools to less than perfect data is not going to fix data deficiencies, to the contrary it is the proverbial hitting of nails with the microscope and can lead to the same kind of outcome – being totally useless (and damage the microscope in the process, lol)A practical, transparent solution is to construct model portfolio benchmarks using public indices and representative asset classes — giving investors and analysts a yardstick to measure relative performance. And while the apparent simplicity can be viewed as a limitation, it can, at the same time, be a powerful benefit because of the efficiency, transparency, and ability to customize and track, provided a proper portfolio construction tool is used that allows for a quick and effective modeling process as well as subsequent updates.

What Is a Model Portfolio Benchmark?

A model portfolio benchmark is a hypothetical blend of commonly available public indices that aims to mirror the risk-return characteristics of a specific alternative strategy or fund.

These benchmarks are:

  • Transparent – based on public indices or ETFs, allowing for ease of data access
  • Customizable – tailored to specific investment mandates, providing flexibility
  • Repeatable – rebalanced consistently for comparison over time

The blend is constructed like a portfolio – with periodic rebalancing, for example, on quarterly basis to ensure consistency of weights over time, creating a return stream that can be used for comparisons and analysis.

Why Use This Approach?
  • Lack of investable alternatives benchmarks: Many alt benchmarks are not replicable or investable, yet investors need a reference for comparison. It is worth noting that efforts are made to create benchmarks for some alternative asset classes (e.g. Refinitiv Private Equity Buyout Index, Nasdaq eVestment Peer Benchmarking, and others).
  • Need for portfolio context: Allocators often compare alternative returns against traditional 60/40 portfolios or cash, which may be misleading, especially as the universe of available alternative investments keeps growing
  • Performance attribution: Helps isolate skill-based alpha from market beta exposures and provide a consistent framework for ongoing monitoring of investment choices
Common Ingredients: Public Proxies for Alts

Here are some widely available indices and ETFs that can be used as building blocks:

Alternative Asset TypePublic ProxyExamples
Private EquityPublic small-cap or growth indicesRussell 2000, S&P 600
Real EstateREIT indicesFTSE Nareit All REITs Index
InfrastructureListed infrastructure ETFsDJ Brookfield Global Infra, iShares IFRA
Private CreditHigh-yield or leveraged loan indicesS&P/LSTA Leveraged Loan Index, HYG ETF
Hedge Funds (Macro, L/S Equity)Multi-asset or factor ETFsSPY (beta), MTUM (momentum), TLT (duration)
CommoditiesCommodity index ETFsDBC, Bloomberg Commodity Index
Venture CapitalNasdaq or thematic tech indicesNasdaq 100, ARKK ETF
How to Build a Model Portfolio Benchmark
Step 1: Define the Strategy Profile

Understand the alternative investments and their role in your investment strategy

  • Target returns and volatility
  • Liquidity profile
  • Sector or factor tilts
  • Geographic or thematic focus
Step 2: Select Public Proxies

Choose a set of public indices or ETFs that capture the above characteristics. Avoid overly granular or niche proxies unless justified.

Step 3: Assign Weights

Start with a strategic mix (e.g., 40% small-cap, 30% REITs, 30% credit). Use:

  • Expert judgment (qualitative match)
  • Historical regression (quantitative fit)
  • Optimization (e.g., minimum tracking error)
Step 4: Rebalance and Maintain

Rebalance quarterly or semi-annually, aligning with the revaluation cycle of the alternative investment. Maintain consistency for meaningful comparisons.

Example: Benchmarking a Private Equity Buyout Fund

Fund Profile: U.S. focused, middle-market buyouts, long duration, equity-like risk.

Model Benchmark:

  • 60% Russell 2000 (small-cap equity proxy)
  • 30% S&P 500 Value (large-cap value component)
  • 10% High Yield Index (for leverage exposure) – we use an approximation ETF for illustration purposes
Chart 1: Ingredient selection for Model Benchmark. Source: AlphaBot

This model benchmark won’t match private equity exactly — but it captures broad exposure to market beta, illiquidity premiums, and leverage-driven returns. This “rough” approximation is exactly the goal due to its simplicity and comparison with the actual fund performance may prove quite revealing and raise important questions (we will touch on that later).

Here is performance chart for the Model Portfolio we generated using AlphaBot:

Chart 2: Model Portfolio performance vs component indices. Source: AlphaBot

The thick blue line is the weighted portfolio – our Model Benchmark. And here are some stats for it:

Chart 3: Model Portfolio key statistics. Source: AlphaBot
Limitations and Considerations
  • Tracking error is inevitable: No proxy can fully replicate private valuations, smoothing, or complexity. However, as you compare the benchmark just created with actual fund returns, reflecting on parameters such as correlations, volatility and relative performance can help ask and understand important questions on the reasons for such differences.
  • Liquidity mismatch: Public proxies are daily-priced, while alt assets are often quarterly. This requires flow planning and crisis management as immediate access to withdrawals (or additional inflows) can be limited
  • Alpha masking: A good benchmark may reduce perceived alpha by better modeling beta exposure — this is a feature, not a bug, and it feeds to the evaluation question we raised above as well

Improving index selection: there is a growing number of specialty indices created to address the void in alternative investments benchmarks, such as Refinitiv Private Equity Buyout Index, Nasdaq eVestment Peer Benchmarking project and others that allow for more accurate representation of certain alternative investment types, or give investors better understanding of where they stand among their peers. These additional indices can also be used in the Model Portfolio approach further improving the results.

Final Thoughts

Model portfolio benchmarks are not perfect, but they’re indispensable for bringing rigor and transparency to alternative investment evaluation. By leveraging commonly available indices and effective tools for portfolio construction investors can better:

  • Contextualize returns
  • Measure value added
  • Communicate performance to stakeholders
  • Focus on making investment decisions instead of spending time on updating countless spreadsheets and reports

In a world where capital is increasingly flowing into non-traditional assets, smart benchmarking is no longer optional — it’s essential. The only thing needed to implement this direct and simple approach is a reliable tool that can manage public daily indices and ETFs, monthly and quarterly fund returns, and ability to mix them into comparisons and portfolios, such as AlphaBot. Empowered with a tool like this, you can start building synthetic benchmark portfolios almost instantly as well as analyze, compare, and model your existing investments performance, entering a new level of understanding the alternative investments universe and your positioning in it. 

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