Asset Allocation. William Kinlaw. Читать онлайн. Newlib. NEWLIB.NET

Автор: William Kinlaw
Издательство: John Wiley & Sons Limited
Серия:
Жанр произведения: Ценные бумаги, инвестиции
Год издания: 0
isbn: 9781119817727
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in passive asset class benchmarks. They then measured the return associated with deviations from the policy mix assuming investment in passive benchmarks, and they attributed this component of return to timing. Finally, they measured the return associated with deviations from the passive benchmarks within each asset class and attributed this component of return to security selection. For each of the 91 funds, they regressed total return through time on these respective components of return. These regressions revealed that asset allocation policy, on average across the 91 funds, accounted for 93.6% of total return variation through time and in no case less than 75.5%.

      Fundamental Flaw

      A Practical View on Importance

      To illustrate our point, consider a portfolio that consists of 75% technology stocks and 25% US bonds. From 2006 to 2013, what percentage of this portfolio's return variation is explained by asset allocation?

      We begin by obtaining monthly historical returns for the actual portfolio. Next, we split the returns into two parts. The first part equals the monthly returns of a portfolio that holds 75% in a broad stock market index and 25% in US bonds. It mimics the asset allocation but ignores security selection. The second part equals the monthly returns of the actual portfolio – which contains a large concentrated position in technology stocks – in excess of the returns of the first part. It reflects the incremental return associated with security selection.

      This separation allows us to decompose the portfolio's monthly return variation into its two component parts. We do so by calculating the fractional contribution to total variance (FCTV), as follows:

      In this example, the asset allocation component appears to explain 73% of the total return variation, dwarfing the 27% explained by security selection. This conclusion mirrors the logic of Brinson, Hood, and Beebower. Intuitively, it seems surprising that such a dramatic security selection tilt carries so little relative importance. In fact, this approach incorrectly implies that asset allocation is more important than security selection because it considers all market volatility to be the result of an asset allocation decision.

Pie chart depicts the fractional contribution to total variance.

      Reductio ad Absurdum

      For example, some investors choose to invest in actively managed funds with high tracking error relative to the norm, but choose an asset mix that is close to the norm, such as the average asset mix of a relevant universe. Other investors choose actively managed funds with low tracking error relative to the norm, but choose an asset mix that is substantially different from the normal asset mix. In the former case, security selection will be seen to be more important than it is normally thought to be, whereas asset allocation will be seen to be less important than it is typically construed to be. In the latter case, the opposite will be true. But these conclusions could be misleading, because they may reflect as much or more about the investors' choices to emphasize asset allocation over security selection than the potential impact asset allocation and security selection have on portfolio performance.