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Asset allocation

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Asset allocation is the strategy an investor uses to distribute his or her investments among various classes of investment vehicles (e.g., stocks and bonds).

A large part of financial planning is finding an asset allocation that is appropriate for a given person in terms of their appetite for and ability to shoulder risk. This can depend on various factors; see investor profile.

Contents

[edit] Justification

Asset allocation is based on the idea that in different years a different asset is the best-performing one. It is difficult to predict which asset will perform best in a given year. Thus, although it is psychically appealing to try to predict the "best" asset, proponents of asset allocation consider it risky. They say that someone who "jumps" from the one asset to another, according to whim, may easily end up with worse results than any consistent plan.

A fundamental justification for asset allocation is the notion that different asset classes offer returns that are not perfectly correlated, hence diversification reduces the overall risk in terms of the variability of returns for a given level of expected return. Therefore having a mixture of asset classes is more likely to meet the investor's goals.

In this respect, diversification has been described as "the only free lunch you will find in the investment game." Academic research has painstakingly explained the importance of asset allocation and the problems of active management (see academics section, below). This explains the steadily rising popularity of passive investment styles using index funds.

Although risk is reduced as long as correlations are not perfect, it is typically forecast (wholly or in part) based on statistical relationships (like correlation and variance) that existed over some historical period. Expectations for return are often derived in the same way.

When such backward-looking approaches are used to forecast forward-looking inputs for return or risk in the traditional mean-variance optimization approach to asset allocation (MVO being the central tenet of Modern Portfolio Theory), the strategy may merely wind up expressing expecations for risk and return in historical terms. As there is no guarantee that past relationships will continue in the future, this is one of the "weak links" in traditional asset allocation strategies as derived from MPT. Other, more subtle weaknesses include the "butterfly effect," by which seemingly minor errors in forecasting lead to recommended allocations that are grossly skewed from investment mandates and/or impractical -- often even violating an investment manager's "common sense" understanding of a tenable portfolio-allocation strategy.

[edit] Examples of asset classes

Sister project Wikibooks has more on the topic of
  • cash (i.e., money market accounts)
  • Bonds: investment grade or junk (high yield); government or corporate; short-term, intermediate, long-term; domestic, foreign, emerging markets
  • stocks: value or growth; large-cap versus small-cap; domestic, foreign, emerging markets
  • real estate
  • foreign currency
  • natural resources
  • precious metals
  • luxury collectables such as art, fine wine and automobiles

To further break down equity investments into additional asset classes consider the following:

Large-Cap
Mid-Cap
Small-Cap
  • By style:
Growth
Blend
Value

Note that 'funds' are not an asset class; funds are filed under what they own, e.g. stocks for stock funds, bonds for bond funds, et cetera.

[edit] Academic studies

In 1986, Brinson, Hood, and Beebower (BHB) published a study about asset allocation of 91 large pension funds measured from 1974 to 1983. [1] They replaced the pension funds' stock, bond, and cash selections with corresponding market indexes. The indexed quarterly return were found to be higher than pension plan's actual quarterly return. The two quarterly return series' linear correlation was measured at 96.7%, with shared variance of 93.6%. A 1991 follow-up study by Brinson, Singer, and Beebower measured a variance of 91.5%. [2] The lessons of the study was that replacing active choices with simple asset classes worked just as well as, if not even better than, professional pension managers. Also, a small number of asset classes was sufficient for financial planning. Financial advisors often pointed to this study to support the idea that asset allocation is more important than all other concerns, which the BHB study lumped together as "market timing". [3] One problem with the Brinson study was that the cost factor in the two return series was not clearly discussed. However, in response to a letter to the editor, Hood noted that the returns series were gross of management fees .[4]

In 1997, William Jahnke initiated debate on this topic, attacking the BHB study in a paper titled The Asset Allocation Hoax. [5] It should be noted that the Jahnke discussion appeared in the Journal of Financial Planning as an opinion piece, not a peer reviewed article. Jahnke's main criticism, still undisputed, was that BHB's use of quarterly data dampens the impact of compounding slight portfolio disparities over time, relative to the benchmark. One could compound 2% and 2.15% quarterly over 20 years and see the sizable difference in cumulative return. However, the difference is still 15 basis points (hundredths of a percent) per quarter; the difference is one of perception, not fact.

In 2000, Ibbotson and Kaplan used 5 asset classes in their study "Does Asset Allocation Policy Explain 40, 90, or 100 Percent of Performance?"[6] The asset classes included were large-cap US stock, small-cap US stock, non-US stock, US bonds, and cash. Ibbotson and Kaplan examined the 10 year return of 94 US balanced mutual funds versus the corresponding indexed returns. This time, after properly adjusting for the cost of running index funds, the actual returns again failed to beat index returns. The linear correlation between monthly index return series and the actual monthly actual return series was measured at 90.2%, with shared variance of 81.4%. Ibbotson concluded 1) that asset allocation explained 40% of the variation of returns across funds, and 2) that it explained virtually 100% of the level of fund returns. Brinson has expressed his general agreement with the Ibbotson-Kaplan conclusions.

In both studies, it is misleading to make statements such as "asset allocation explains 93.6% of investment return". [7] Even "asset allocation explains 93.6% of quarterly performance variance" leaves much to be desired, because the shared variance could be from pension funds' operating structure. [8] Hood, however, rejects this interpretation on the grounds that pension plans in particular cannot cross-share risks and that they are explicitly singular entities, rendering shared variance irrelevant.[9] The statistics were most helpful when used to demonstrate the similarity of the index return series and the actual return series.

A 2000 paper by Meir Statman found that using the same parameters that explained BHB's 93.6% variance result, a hypothetical financial advisor with perfect foresight in tactical asset allocation performed 8.1% better per year, yet the variance was still explained 89.4% of the variance. [10] Thus, explaining variance does not explain performance. Statman says that strategic asset allocation is movement along the efficient frontier, whereas tactical asset allocation involves movement of the efficient frontier. A more common sense explanation of the Brinson, Hood, and Beebower study is that asset allocation explains more than 90% of the volatility of returns of an overall portfolio, but will not explain the ending results of your portfolio over long periods of time. Hood notes in his review of the material over 20 years, however, that explaining performance over time is possible with the BHB approach but was not the focus of the original paper.[11]

Bekkers, Doeswijk and Lam (2009) investigate the diversification benefits for a portfolio by distinguishing ten different investment categories simultaneously in a mean-variance analysis as well as a market portfolio approach. The results suggest that real estate, commodities and high yield [Is there a word missing after "high yield"?] add most value to the traditional asset mix of stocks, bonds and cash. A study with such a broad coverage of asset classes has not been conducted before, not in the context of determining capital market expectations and performing a mean-variance analysis, neither in assessing the global market portfolio.[12]

[edit] Performance indicators

McGuigan described an examination of funds that were in the top quartile of performance during 1983 to 1993. [13] During the second measurement period of 1993 to 2003, only 28.57% of the funds remained in the top quartile. 33.33% of the funds dropped to the second quartile. The rest of the funds dropped to the third or fourth quartile.

In fact, low cost was a more reliable indicator of performance. Bogle noted that an examination of 5 year performance data of large-cap blend funds revealed that the lowest cost quartile funds had the best performance, and the highest cost quartile funds had the worst performance. [1]

[edit] Return versus risk trade-off

In asset allocation planning, the decision on the amount of stocks versus bonds in one's portfolio is a very important decision. Simply buying stocks without regard of a possible bear market can result in panic selling later. One's true risk tolerance can be hard to gauge until having experienced a real bear market with money invested in the market. Finding the proper balance is key.

Cumulative return after inflation from 2000-to-2002 bear market [14]
80% stock / 20% bond -34.35%
70% stock / 30% bond -25.81%
60% stock / 40% bond -19.99%
50% stock / 50% bond -13.87%
40% stock / 60% bond -7.46%
30% stock / 70% bond -0.74%
20% stock / 80% bond +6.29%
Projected 10 year Cumulative return after inflation
(stock return 8% yearly, bond return 4.5% yearly, inflation 3% yearly [15]
80% stock / 20% bond 52%
70% stock / 30% bond 47%
60% stock / 40% bond 42%
50% stock / 50% bond 38%
40% stock / 60% bond 33%
30% stock / 70% bond 29%
20% stock / 80% bond 24%

The tables show why asset allocation is important. It determines an investor's future return, as well as the bear market burden that he or she will have to carry successfully to realize the returns.

[edit] See also

[edit] Footnotes

^  Stock return from a Wilshire 5000 index fund; bond return from a Lehman Aggregate Bond Index fund; inflation data from US Treasury Department.

^  Input parameters are for illustration purpose only; actual returns will vary.

[edit] References

^  Gary P. Brinson, L. Randolph Hood, and Gilbert L. Beebower, Determinants of Portfolio Performance, The Financial Analysts Journal, July/August 1986.

^  Gary P. Brinson, Brian D. Singer, and Gilbert L. Beebower, Determinants of Portfolio Performance II: An Update, The Financial Analysts Journal, 47, 3 (1991)

^  William Jahnke, The Asset Allocation Hoax, Journal of Financial Planning, February 1997

^  Roger G. Ibbotson and Paul D. Kaplan, Does Asset Allocation Policy Explain 40%, 90%, or 100% of Performance?, The Financial Analysts Journal, January/February 2000

^  Thomas P. McGuigan, The Difficulty of Selecting Superior Mutual Fund Performance, Journal of Financial Planning, February 2006

^  James Dean Brown, The coefficient of determination, Shiken: JALT Testing & Evaluation SIG Newsletter, Volume 7, No. 1, March 2003

^  Meir Statman, The 93.6% Question of Financial Advisors, Journal of Investing, Spring 2000

^  L. Randolph Hood, Response to Letter to the Editor, The Financial Analysts Journal 62/1, January/February 2006

^  L. Randolph Hood, Determinants of Portfolio Performance - 20 Years Later, The Financial Analysts Journal 61/5 September/October 2005

^  Bekkers Niels, Doeswijk Ronald Q. and Lam Trevin W., [http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1368689 Strategic Asset Allocation: Determining the Optimal Portfolio with Ten Asset Classes ], Working Paper Series, March 2009>

  1. ^ brinson1
  2. ^ bsb
  3. ^ statman
  4. ^ hood
  5. ^ jahnke
  6. ^ ibbot1
  7. ^ brown
  8. ^ ibbot1
  9. ^ hood
  10. ^ statman
  11. ^ hood1
  12. ^ bdl
  13. ^ mcguigan
  14. ^ table1
  15. ^ table2

[edit] External links

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