Earning a Place in the Portfolio: Using Implied Returns in TPA Decisions

One of the most powerful ideas at the heart of the total portfolio approach (TPA) is the principle of best use of capital regardless of asset class. In contrast to traditional strategic asset allocation — where capital is pre-allocated into silos such as equities, bonds or private markets — a TPA encourages investors to manage the portfolio as a unified whole. Under this philosophy, every investment must “earn its place” in the portfolio based on its contribution to total portfolio goals, not just relative performance within an asset class. 

This approach supports dynamic capital deployment, responsiveness to changing market conditions and alignment with long-term investment beliefs and total fund goals. However, putting this idea into practice presents several challenges — particularly when comparing investment opportunities across diverse asset classes that differ in terms of liquidity, risk profile, performance metrics and evaluation frameworks.  

Without a common metric to determine whether existing investments are “worth the risk” or if a new investment may meaningfully improve portfolio efficiency, decisions can easily be driven by internal constraints or siloed mandates, rather than portfolio-level priorities. We propose and evaluate a framework based on implied returns and hurdle rates to help asset owners and other decision makers as they manage portfolios. 

Simply put, implied return is the return that each current portfolio component must be expected to deliver for the portfolio, given how much risk the asset owner is willing to take and how the assets move together. More technically, implied returns use the current portfolio weights and the covariance matrix of asset returns to infer what return each asset must deliver to make the current portfolio optimal.¹ 

Risk practitioners have long compared assets using marginal risk contributions, risk budgets and a variety of risk-adjusted metrics. These are often expressed in risk units, which portfolio managers may find abstract. Implied return translates complex metrics into a single, intuitive number for front-office decision makers.  

Because they are based on the covariance matrix, implied returns naturally incorporate each investment’s volatility and correlation with the rest of the portfolio. This means they implicitly account for exposure to common macro, factor and any other risks shared across asset classes, making implied returns especially useful in a TPA framework. They can be used to assess whether an existing investment’s expected return is high enough to justify its overlap, or concentration with existing portfolio risks.  

The same concept may be used to determine whether the expected return of a potential new investment is high enough to justify its standalone risk and interaction with the rest of the portfolio. Hurdle-rate return is the minimum return an asset not held in the portfolio would need to offer to be worth adding, given its risk and correlation with what you already own. In other words, if a new asset can’t meet its hurdle rate it won’t improve the portfolio.² 

This hurdle rate can be calculated with inputs from the MSCI Multi Asset Class (MAC) Factor Model:  

Hurdle Rate = Beta × Portfolio Expected Return 

The beta reflects the new investment’s volatility and correlation with the portfolio. The higher the beta, the greater the return required to justify the allocation. This structure ensures that investments are evaluated not only on their standalone performance, but also on their portfolio fit: Do they diversify risks, or add more of the same?  

The asset owner likely has a forecast for the new investment’s expected return based on capital market assumptions (CMA), often derived from a model such as the MSCI Macro Finance Model. 

Consider a hypothetical Japanese asset owner evaluating whether to add global real estate to a traditional portfolio equally weighted across global and domestic equities and bonds. The MSCI MAC Factor Model’s (MAC.XL) forecast of portfolio risk is 10.27%, as of Dec. 31, 2024. In practice, portfolio expected returns would typically be derived bottom-up from CMAs, but, for simplicity we assume the portfolio has an expected return of 4.11%, giving it a Sharpe Ratio of 0.4.  

We created custom versions of the MSCI JPY Government Bond and MSCI ex-JPY Government Bond Indexes by carving out JPY and ex-JPY portions from the MSCI Developed Market Government Bond Index and re-normalizing the weights to 100%.

Ơ is total portfolio risk; α is portfolio implied return computed as assumed Sharpe Ratio (0.4) multiplied by total portfolio risk (α=0.4Ơ). 

We can use the MSCI MAC Model to assess the risk profile of the MSCI Global Annual Property Index —its forecast risk (13.58%) and correlation to the current portfolio (0.78).³ Multiplying those two numbers and dividing by the portfolio volatility (10.27%), gives a beta of 1.03 to the current portfolio. Given the portfolio’s expected return of 4.11%, this implies a hurdle rate of 4.25% for the potential real estate allocation (1.03 * 4.11%).

The final step is to compare this hurdle rate to the expected return for the real estate allocation (from either the fund manager or the asset owner’s internal assessment), making any needed adjustments for illiquidity by applying a liquidity premium to reflect the higher risk and opportunity cost. If the expected return is higher than the hurdle rate, the real estate asset has earned its place in the portfolio.

In practice, asset owners can account for liquidity using a heuristic (e.g., adding a liquidity premium to the hurdle rate), or a model-based approach, such as one that estimates illiquidity premia based on asset cash flows and risk characteristics.⁴ Either approach will result in an upward adjustment of the hurdle rate for private market investments.

In a world of increasingly complex portfolios, a unified capital allocation process is both a philosophical imperative and a practical challenge. By using implied returns to facilitate capital allocation decisions and compute hurdle rates, asset owners can create a disciplined, transparent and adaptable framework for evaluating investment opportunities across asset classes and across teams. 

This approach operationalizes the total portfolio mindset by:  

• Encouraging portfolio-wide thinking by focusing on total fund outcomes 
• Providing a common metric that can be used to compare public and private investments 
• Helping teams speak a shared language of risk and return across asset classes 
• Balancing portfolio construction goals with investment-level characteristics