Asset allocation

Describe and explain asset allocation and its importance in reaching one s financial goals. 

Asset allocation does not assure or guarantee better performance and cannot eliminate the risk of investment losses. 

Studies have consistently shown that selection of the asset mix is the most important determinant of investment performance. Early influential research by Brinson et al. (1986, 1991) and a more recent update by Ibbotson and plan (1999) indicate that asset allocation explains up to 90% of portfolio returns. Security selection and other factors explain the remainder. Consequently, the asset blend is the key intellectual challenge for investment managers and should receive the most attention. Traditional rules of thumb no longer work in a dynamic world with many choices and unexpected risks. 

Markowitz was the first to propose an explicit quemtification of the asset-allocation problem (Markowitz 1959). Three categorical inputs are required the expected return for each asset in the portfolio, the risk or variance of each asset s return, and the correlation between asset returns. The objective is to select the optimal weights for each asset that meiximizes total portfolio return for a given level of portfoho risk. The set of optimum portfohos over the risk spectrum traces out what is called the efficient frontier. 

To illustrate the essence of the asset-allocation problem, 1 begin with a simple example theit includes the following assets U.S. stocks, intemationeil stocks, U.S. bonds, international bonds, and cash. This constitutes a broad asset mix typical of that used by many professional managers. Expected returns are 11.0%, 12.6%, 6.0%, 6.9%, and 5.0%, respectively. The expected standard deviations (risk) of these returns are 12.5%, 14.7%, 4.3%, 7.8%, and 0.0%. Note that the standard deviation of cash returns is zero because this asset is presumed to consist of riskless U.S. Treasury securities. The correlation matrix for asset returns is ... 

As an example of the extrapolation faUacy, consider portfolio performance over the last two decades. If one constructed an efficient portfoUo in 1990 bas on the 1980s history, laige allocations would have been made to international equities. This is primarily due to the fact that lapanese stocks produced the best returns in the woild up to 1989. Yet in the 1990s, Japanese equities feU by more than 50% from their 1989 peak, and the best asset allocation would have been to U.S. equities. Using the 1980s history to construct MV portfoUos would have produced dismal portfoUo returns (Table 3). 

The primary distinction between asset selection and asset allocation is that the thought processes differ. In asset selection, a manager focuses on defining the candidate universe broadly. In asset allocation, assets are typically viewed as given and the effort is on forecast accuracy. 

Finally, there are a number of structured derivative products often marketed as new asset classes. Such products are usually perturbations of existing assets. For example, enhanced index products are typictdly a weighted combination of exposure to a specific equities or bond class, augmented with exposure to a particular hedge fund strategy. Similarly, yield-enhanced cash substitutes with principal guarantee features are composed of zero coupon Treasuries with the residual cash invested in options or other derivatives. Such products are part hedge fund and part primary asset from an allocation perspective and are better viewed as implementation vehicles rather than incorporated exphcitly in the asset allocation. 

Beyond asset selection, the key to successful investment performance via MV asset allocation depends largely on the accuracy of return, risk, and correlation forecasts. These forecasts may be subjective or quantitative. A subjective or purely judgmental approach allows one the luxury of considering any number of factors that can influence returns. The disadvantage of pure judgment is that it is sometimes nebulous, not always easily explained, and may sometimes be theoretically inconsistent with macroeconomic constraints. 

The discussion so far has focused on asset allocation as generally applicable to a broad cross-section of investors. In reality, the vast majority of individual investors face special restrictions that limit their flexibility to implement optimal portfolios. For example, many investors hold real estate, concentrated stock holdings, VC or LBO partnerships, restricted stock, or incentive stock options that for various reasons cannot be sold. For these investors, standard MV optimization is stiU appropriate and they are weU advised to target the prescribed optimum portfolio. They should then utilize derivative products such as swaps to achieve a synthetic replication. 

Taxes are largely immaterial for pension funds, foundations, endowments, and offshore investors because of their exempt status. Mean-variance asset allocation can be applied directly for these investors as already described. However, for domestic investors, taxes are a critical issue that must be considered in modeling investment choices. 

Duarte also proposes a generalized approach to asset allocation that includes mean semi-variance, mean absolute deviation, MV, and value-at-risk as special cases. While cleverly broad, Duarte s method relies on simulation teclmiques and is computationally burdensome. In addition, because simulation approaches do not have explicit analytical solutions, the technique loses some of the precision of MV analysis. For example, one can examine solution sensitivities from the second-order conditions of MV problems, but this is not so easy with the simulation. It remains to be seen whether simulation approaches receive widespread acceptance for solving portfolio problems. Nonetheless, simulation techniques offer tremendous potential for future applications. 

Ibbotson, R., and Kaplan, P. (1999), Does Asset Allocation Explain 40%, 90%, or 100% of Performance unpubhshed paper, Ibbotson Associates, April. 

Lamm, R. M. (1998a), Asset Allocation Implications of Inflation-Protection Securities Adding Real Class to Portfolios, Journal of Portfolio Management, Vol. 24, No. 4, pp. 93-100. 

Sharpe, W. (1992), Asset Allocation Management Style and Performance Measurement, Journal of Portfolio Management, Vol. 18, No. 2, pp. 7-19. 

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Asset allocators/financial engineers who use futures contracts to manipulate the payoff profiles of bonds or other specially constructed portfolios. 

An asset allocation manager, with both bonds and equity in the portfolio for which she is responsible, anticipated the slump in share prices before a large downturn in prices had occurred. She switched out... 

Asset allocation decisions by credit quality are similar to those for the yield curve but with an added dimension. When spreads widen, typically the lowest rated credits widen the most, and the spread differential between the triple-A and triple-B rated bonds increase, the opposite happens in cases where spreads tighten. Therefore, a portfolio with lower credit risk will generally outperform in a spread widening environment and vice versa. 

Operations plan (OPLAN)—plan developed by and for each federal department or agency describing detailed resource, personnel, and asset allocations necessary to support the concept of operations detailed in the concept plan. 

The design of a web-based personal asset allocation system... 

Personal asset allocation This determines the strategic asset allocation decisions. Users are asked to specify their targets, their planning horizon, and the availability of funds. The users must also reveal their attitude towards risk. A scenario optimization model (see Consiglio et al., 2002 Consiglio et al., 2001) specifies an asset allocation plan that meets the target using the available endowment, and which is consistent with the user s risk profile. 

The system resulting from the combination of technology and business plans adds value at two levels. At a basic level it supports the provision of personal asset allocation advise to consumers. At an advanced level it supports the complex needs of financial advisors in serving their clients, designing customized portfolios, and dealing with the product originators. Depending on the business plan of each client institution the system would add value at either one, or at both levels. 

The third user is a new virtual Bank set up recently by one of the major Banks in Northern Italy with the widest country-wide reach. The web-based system has been adopted as part of their core-business and is an integral part of the services offered by this virtual bank. The Bank is completely independent from the Northern Italian bank and is, in a sense, competitor to the parent company. The view adopted by the new bank is that virtual banking should not focus only on the electronic provision of traditional banking services — deposits, credit cards, account payments etc.— but must offer new services in a seamless environment. The web-based personal asset allocation system provides a service not offered by most retail Banks which integrates naturally with the core business of electronic banking. The Bank uses the web-based system at the basic level offering one more service to its clients. In doing so it must be noted that it competes with the parent company. 

Consiglio, A., F. Cocco and S.A. Zenios, www.Personal Asset Allocation, Interfaces, (to appear). 

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