Strategic Asset Allocation

Design strategic asset allocation frameworks for private markets with transparent assumptions, scenario analysis, and institutional governance.

Methodology Preview

Efficient Frontier (Simplified)

Institutional investors know how to optimize portfolios in public markets, because prices are continuous and risk can be measured consistently. In private markets, this is harder: cashflows are irregular, transparency is limited, and direct comparability across funds is low.

QFT addresses this by translating private-market behavior into comparable risk/return signals and linking them to public-market reference structures. The chart below shows that logic in a simplified way: from many feasible portfolio outcomes to an efficient frontier, concrete allocation choices, and a cash-funded path toward the optimized portfolio.

Source Summary

Simulated portfolios (raw): 20,000

Frontier points (upper boundary): --

Frontier points (lower boundary): --

Additional commitment modeled: USD 30m

Strategic Asset Allocation for Private Markets

Strategic Asset Allocation (SAA) is the policy layer of a long-term portfolio. It defines how much risk to take, where to allocate capital across asset classes, and how to keep decisions consistent across market cycles. In private markets, this is especially important because commitment pacing, liquidity, and manager selection are tightly linked.

QFT provides a quantitative SAA framework designed for institutional investors who need more than broad heuristics. The objective is simple: build a private-markets allocation that is robust, comparable, and implementable.

Why This Is Hard In Private Markets

  • There are no continuous market prices for most private assets.
  • Cashflows are irregular and fund vintages are not directly comparable.
  • Liquidity risk builds over time through commitments, not only through mark-to-market volatility.
  • Traditional public-market optimization methods are often transferred without sufficient adaptation.

How The QFT SAA Framework Works

1. Cashflow-Based Risk/Return Modeling

We model private assets from observed capital calls and distributions, not from smoothed assumptions alone. This improves comparability across funds and creates a more realistic basis for long-term portfolio construction.

2. Public-Market Reference Mapping

Using similarity models across categorical and numerical deal/fund features, private exposures are mapped to relevant public-market reference portfolios. This creates a common measurement basis for cross-asset decisions.

3. Scenario And Liquidity Engine

Allocation alternatives are tested under multiple market regimes and pacing paths. The focus is not only expected return, but also drawdown behavior, deployment speed, and liquidity pressure over time.

4. Governance-Ready Decision Output

The result is a transparent allocation policy with explicit assumptions, trade-offs, and constraints. This makes investment committee discussions faster, clearer, and more defensible.

What This Helps You Decide

  • Target allocation ranges across buyout, growth, venture, private debt, infrastructure, and public-market sleeves
  • Commitment pacing under different liquidity and deployment assumptions
  • How much risk is truly compensated versus concentrated or unrewarded
  • When a portfolio shift is strategic (policy-driven) versus tactical (short-term noise)

Strategic Rather Than Tactical

This framework is built for long-term policy decisions, not short-term market timing. We review assumptions systematically and rebalance with discipline, while avoiding reactive allocation changes driven by temporary narratives.

Outcome For Investment Teams

Teams receive a practical SAA blueprint: target weights, pacing guidance, scenario diagnostics, and an audit trail of the underlying rationale. It connects mandate-level objectives with manager-level implementation, so strategy, execution, and governance remain aligned.