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Elements of portfolio construction

Vanguard’s portfolio construction framework is built on long-held investing principles. Watch this short video with Roger Aliaga-Díaz, Vanguard’s global head of portfolio construction and chief economist, Americas, on the primary elements involved in determining a customized portfolio.
Transcript
Video Length: 04:10

Lara de la Iglesia: So, Roger, Vanguard has initiated a portfolio construction framework. Can you talk about the different elements of the framework and what guides it?

Roger Aliaga-Díaz: Yes, definitely. Our portfolio construction framework is grounded in the four principles of investing success, our basic foundation of portfolio thinking: have clear goals, balance, be mindful of costs, and discipline, right?

So within that we basically adopt a two-step approach. First, inputs, goals aligning to those principles. Then investor beliefs and preferences such as ESG preference—environmental, social, governance—or conviction in an active manager. And what are the asset classes that the portfolio needs in order to fulfill those goals, right?

Lara de la Iglesia: Yes.

Roger Aliaga-Díaz: So that's the first step. The second step is the investment methodology step. This is more the quantitative step. This is where the portfolio math is performed to find an appropriate balance of risks and asset returns. Going back to the other principle of balance, right?

Lara de la Iglesia: Yes.

Roger Aliaga-Díaz: So there are four methodologies that are included in this framework – market-cap, which is well known; market-capitalization indices, mostly stock and bonds – betas. The second methodology is models-based SAA, or strategic asset allocation. Here we go a little bit more granular inside those betas. So we look at segments of equity market, value, growth, perhaps long-term bonds versus credit. We go into other type of assets such as TIPS, inflation-linked securities, commodities, and so on, right? And this methodology requires the help of models like the Vanguard's Capital Markets Model, the VCMM.

The third one, active-passive. This is when we bring in active investments. We look at the active risks of those investment versus the potential for a performance and try to solve for an optimal mix of active and passive, right? So we answer the question how much active in our portfolio.

And the fourth and last is time-varying asset location, similar to models-based SAA. We use the VCMM, but we look at the medium-term forecast—10-year horizon. And those VCMM forecasts tend to respond to market conditions such as equity valuations, interest rates. So those returns will move, and as a result, the portfolio that comes out of it will be time-varying, right?

So we cover a full set of options that give us that portfolio solutions, depending on what are the different settings in step 1 and step 2.

Notes:

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The Vanguard Capital Markets Model® is a proprietary financial simulation tool developed and maintained by Vanguard’s primary investment research and advice teams. The model forecasts distributions of future returns for a wide array of broad asset classes. Those asset classes include U.S. and international equity markets, several maturities of the U.S. Treasury and corporate fixed income markets, international fixed income markets, U.S. money markets, commodities, and certain alternative investment strategies. The theoretical and empirical foundation for the Vanguard Capital Markets Model is that the returns of various asset classes reflect the compensation investors require for bearing different types of systematic risk (beta). At the core of the model are estimates of the dynamic statistical relationship between risk factors and asset returns, obtained from statistical analysis based on available monthly financial and economic data from as early as 1960. Using a system of estimated equations, the model then applies a Monte Carlo simulation method to project the estimated interrelationships among risk factors and asset classes as well as uncertainty and randomness over time. The model generates a large set of simulated outcomes for each asset class over several time horizons. Forecasts are obtained by computing measures of central tendency in these simulations. Results produced by the tool will vary with each use and over time.

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