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The strong dollar. Why and how long?

Time-varying asset allocation is a portfolio construction methodology that makes room for allocation changes over medium-term timeframes as market conditions change. By contrast, tactical asset allocations can shift within days or hours. In this video, Roger Aliaga-Díaz, Vanguard’s global head of portfolio construction and chief economist, Americas, explains how they compare.
Transcript
Video Length: 3:59

Lara de la Iglesia: Roger, tell me what is the difference between time-varying asset allocation and tactical asset allocation?

Roger Aliaga-Diaz: Definitely. Sometimes it's better to define something by what it is not. So in that sense, a TVAA or time-varying asset allocation is deeper than tactical asset allocation. So let me draw the contrast a little bit here.

Tactical asset allocation or TAA for short, relies on market timing, on actually precise market timing. Right, pinpoint focus accuracy, very short-term bets, have to play out within days or hours even. And the other thing with TAA is that TAA managers basically claim to have superior information about the markets than everyone else. That's because, in order to outperform peers, right?

Also, one third aspect of TAA is that when done, basically, in a more informal approach because we find intermediaries sometimes, there is no systematic repeatable process. It's more based on portfolio goals and discretional portfolio recommendations. And that, basically, because it can cause problems from a risk-management perspective, right, there is too much focus on return maybe, and therefore risk.

So let's bring it back now to our time-varying asset allocation. Time-varying asset allocation does not rely on market timing. It relies on the VCMM forecast.

Lara de la Iglesia: Vanguard's Capital Markets Model®.

Roger Aliaga-Diaz: Which is the Vanguard's Capital Markets Model and basically those forecasts are longer term, in the five- to ten-year timeframe, and also we like to say they are done in a distributional framework, which essentially means that we account for the possibilities that the model may be wrong at times.

Right, so on average we think it would be right over longer stretches of time, but certainly there are forecast error and risk, and risk basically is really a part of the portfolio construction process there.

The other thing with the Vanguard Capital Markets Model, the VCMM, is that it doesn't require to have basically superior information from the market. In fact, it does rely on public information such as the state of the markets, equity valuations, interest rates. So we use those pieces of information that are available to everyone else, but we do draw in some systematic correlations that exist between those market conditions and the general direction of asset returns over the next few years.

Lara de la Iglesia: Yes.

Roger Aliaga-Diaz: Right, so there is well-established research that shows that you can actually, not perfectly but directionally accurately, tell where asset returns might be going on average over longer stretches of time when we see certain market conditions. So think of the dot.com bubble in 1999, right, and the ten-year period of very low equity returns that happened after that.

So our model has warned us about the low returns, returns lower than normal. So with all this into our portfolio construction, definitely there are risks, as I said before, and that's why TVAA is not for everyone. 

There has to be a clear understanding of what are the trade-offs involved. In short, TVAA takes a form of active risk in the form of forecast, a modern model forecast risk. But some investors feel comfortable with that, and they prefer to have a clear line of sight to the market conditions to feel good with those changes in the portfolio.

Notes:

All investing is subject to risk, including the possible loss of the money you invest. Be aware that fluctuations in the financial markets and other factors may cause declines in the value of your account. There is no guarantee that any particular asset allocation or mix of funds will meet your investment objectives or provide you with a given level of income.

IMPORTANT: The projections and other information generated by the Vanguard Capital Markets Model regarding the likelihood of various investment outcomes are hypothetical in nature, do not reflect actual investment results, and are not guarantees of future results. VCMM results will vary with each use and over time.

The VCMM projections are based on a statistical analysis of historical data. Future returns may behave differently from the historical patterns captured in the VCMM. More important, the VCMM may be underestimating extreme negative scenarios unobserved in the historical period on which the model estimation is based.

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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