William Kinlaw - Asset Allocation

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Asset Allocation: краткое содержание, описание и аннотация

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Discover a masterful exploration of the fallacies and challenges of asset allocation In
—the newly and substantially revised
of
—accomplished finance professionals William Kinlaw, Mark P. Kritzman, and David Turkington deliver a robust and insightful exploration of the core tenets of asset allocation.
Drawing on their experience working with hundreds of the world’s largest and most sophisticated investors, the authors review foundational concepts, debunk fallacies, and address cutting-edge themes like factor investing and scenario analysis. The new edition also includes references to related topics at the end of each chapter and a summary of key takeaways to help readers rapidly locate material of interest.
The book also incorporates discussions of:
The characteristics that define an asset class, including stability, investability, and similarity The fundamentals of asset allocation, including definitions of expected return, portfolio risk, and diversification Advanced topics like factor investing, asymmetric diversification, fat tails, long-term investing, and enhanced scenario analysis as well as tools to address challenges such as liquidity, rebalancing, constraints, and within-horizon risk. Perfect for client-facing practitioners as well as scholars who seek to understand practical techniques,
is a must-read resource from an author team of distinguished finance experts and a forward by Nobel prize winner Harry Markowitz.

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We measure the importance of choosing between asset class A and asset class B the same way, but first we must calculate the standard deviation of each asset class. If we assume the individual securities are weighted equally within each asset class, the standard deviation of asset class A equals

(3.3) Here equals the standard deviation of asset class A equals the stand - фото 46

Here, картинка 47equals the standard deviation of asset class A, картинка 48equals the standard deviation of A1, картинка 49equals the standard deviation of A2, and картинка 50is the correlation between A1 and A2.

We repeat the same calculation to derive the standard deviation of asset class B.

The relative volatility between asset class A and asset class B equals

(3.4) TABLE 31Standard Deviation Correlation and Relative Volatility Standard - фото 51

TABLE 3.1Standard Deviation, Correlation, and Relative Volatility

Standard Deviation (%) Correlation (%) Relative Volatility (%) Standard Deviation (%) Correlation (%) Relative Volatility (%)
A1 10.0 A1 10.0
A2 10.0 0.0 14.1 A2 10.0 50.0 10.0
B1 10.0 B1 10.0
B2 10.0 0.0 14.1 B2 10.0 50.0 10.0
A 7.1 A 8.7
B 7.1 0.0 10.0 B 8.7 50.0 8.7
Standard Deviation (%) Correlation (%) Relative Volatility (%) Standard Deviation (%) Correlation (%) Relative Volatility (%)
A1 10.0 A1 10.0
A2 10.0 50.0 10.0 A2 10.0 50.0 10.0
B1 10.0 B1 10.0
B2 10.0 50.0 10.0 B2 10.0 50.0 10.0
A 8.7 A 8.7
B 8.7 33.3 10.0 B 8.7 25.0 10.6

In Equation 3.3, картинка 52equals the relative volatility between A and B, картинка 53equals the standard deviation of A, картинка 54equals the standard deviation of B, and картинка 55is the correlation between A and B.

Suppose the four securities are uncorrelated with each other. Then security selection would be more important than asset allocation because the asset classes would be less risky than the average risk of the securities they comprise, which results in less relative volatility between the asset classes than between the securities within each asset class. Moreover, as more securities are added, the asset class standard deviations decline further, which in turn further reduces the relative volatility between the asset classes. If, for example, security returns are uncorrelated and the securities are equally weighted, then the asset class standard deviation diminishes with the square root of the number of securities included. It is only when the correlation between asset classes A and B is substantially less than the correlation between the individual securities within the asset classes that the relative volatility between asset classes is greater than the relative volatility between securities. These relationships are illustrated in Table 3.1.

The upper left panel shows that relative volatility between asset classes is less than relative volatility between securities when they are all uncorrelated with one another. The upper right panel shows the same result when they all are equally correlated with one another. The lower left panel shows the asset class and security correlations that lead to convergence between relative volatilities. Finally, the lower right panel provides an example in which the relative volatility between asset classes is higher than it is between securities.

Determining Relative Importance by Simulation

The associations between standard deviation, correlation, and relative volatility are easy to illustrate when we consider only two asset classes each divided equally between only two securities. These associations become less clear when we consider several asset classes weighted differently among hundreds of securities with a wide range of volatilities and correlations. Under these real-world conditions, it is easier to resolve the question of relative importance by a simulation procedure known as bootstrapping.

Unlike Monte Carlo simulation, which draws random observations from a prespecified distribution, bootstrapping simulation draws random observations with replacement from empirical samples. Specifically, we generate thousands of random portfolios from a large universe of securities that vary only because of asset allocation or security selection. This allows us to observe the distribution of available returns associated with each investment decision as opposed to studying the actual performance of managed funds, which reflects the biases of their investors. Kritzman and Page (2002) conducted such an analysis for investment markets in five countries: Australia, Germany, Japan, the United Kingdom, and the United States based on returns from 1988 to 2001. They showed that the dispersion around average performance arising from security selection was substantially greater than the dispersion arising from asset allocation in every country, and it was particularly large in the United States because the United States has a larger number of individual securities. 5

L'Her and Plante (2006) refined the Kritzman and Page methodology to account for the relative capitalization of securities, and they also included a broader set of asset classes. Their analysis showed asset allocation and security selection to be approximately equally important – still a far different result from the conclusion of Brinson, Hood, and Beebower.

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