Naïve Diversification and Heuristics

Benartzi and Thaler (2001) investigated diversification strategies as part of an investor’s asset allocation decision. They found evidence to suggest that people use ‘rules of thumb’ to determine their asset allocations. This approach is also expressed by the authors as a ‘diversification heuristic’ or ‘naive’ diversification. Shefrin (2002, p. 14) describes heuristics as “…back of envelope calculations that come close to providing the right answer” and warned that “…heuristics may involve bias, meaning they may tend to be off target in a particular direction…”

Benartzi and Thaler (2001) showed that some investors follow the ‘1/n strategy’ in that they divide their contributions evenly across the funds offered by the plan. They

argue that naïve diversification could be costly in that the portfolio may not be efficient or it may not meet the risk profile of the individual. They further argue that the 1/n strategy may still produce reasonable diversification outcomes but “it does not assure sensible or coherent decision-making” (Benartzi & Thaler 2001, p. 96). They also show that plan design has a significant influence on the asset allocation outcomes of individuals. If the plan offers more bond funds and few equity options then the investor will create a conservative portfolio. On the other hand, a higher number of equity fund options will result in the investor’s portfolio being substantially more aggressive. These outcomes may not necessarily suit the individual’s requirements. For example, younger individuals may create a conservative portfolio when a more aggressive approach might be required.

Liang and Weisbenner (2002) found that retirement plan characteristics strongly influenced investment decisions by participants. They also found evidence to support the concept of naïve diversification. More specifically, they were able to show that when presented with more investment options, plan participants tend to follow the 1/n rule.

In contrast to the above studies Huberman and Jiang (2006) draw their data set from archives of individual records of 401(k) plans rather than aggregate-level data analysis. Support was found for the 1/n heuristic, but this support was weaker when more funds were offered to participants. The data revealed that participants mostly used three to four funds in their plans, regardless of the number of fund choices available. However, their evidence provided no support for framing effects. That is, a higher level of equity fund options offered did not significantly influence participants to have proportionally higher portfolio weightings in equity. The authors therefore conclude from their results that investors do not deviate from “rational choice”. In these circumstances rational choice is best described as consistency in behaviour regardless of the amount and variation of fund options offered to participants. However, the alternative conclusions put forward in this study were qualified where it was stated by Huberman and Jiang (2006, p. 797) that it:

Using multi-period data (panel data) of 401(k) plans from the US, Brown, Liang and Weisbenner (2007) found that asset allocation decisions of participants were influenced by both the number and mix of investments options made available to them. Similar to the findings of Benartzi and Thaler (2001) their evidence suggests that an additional equity fund option will result in an overall increase in participant allocations to this asset class. This was also found to be the case for additional options in other asset classes such as company stock, fixed income funds and balanced funds. Brown, Liang and Weisbenner (2007, p. 2011) conclude that:

This strongly suggests that average participants are not optimally allocating their portfolios according to standard finance theory predictions, but instead are following naïve strategies that subject them to manipulation by non-binding changes in the number and mix of investment options.

An Australian study by Gerrans, Clark-Murphy and Speelman (2006) examined decisions by members of an industry superannuation fund (Health Employees Superannuation Trust Australia (HESTA) for the period July 2003 to December 2004. The superannuation fund offered members a total of 14 investment options. These included six ready-made investment plans and eight single asset classes. The ready- made plans were based on strategic asset class allocations and varied from funds comprising shares only to more balanced funds. It was found that the majority of choices involved only ready-made investment plans and that almost a quarter of the members made a change to allocate their funds across more than one ready-made investment plan. Gerrans et al. (2006, p. 14) suggest “a possibly naïve view of diversification unless members are conscious of resulting asset allocation”.

The implications of financial behaviour when it comes to retirement savings decisions was emphasised by Kahneman (2003, p. 1468) in his Nobel lecture where he refers to the study of Benartzi and Thaler (2001) as part of a:

…growing literature of field research and field experiments that documents large and systematic mistakes in some of the most consequential financial decisions that people make, including choices of investments…

VanDerhei, Holden, Alonso and Copeland (2008) provide 2007 data indicating that more recently employed individuals are investing their 401(k) assets in balanced funds, including life-cycle funds. This increase in participation in balanced funds was also evident among recently employed young workers. This provides evidence that increasing numbers of workers in 401(k) plans may be seeking balance or diversification within their investments.

McClatchey and VandenHul (2005) using a rolling period optimisation model, created portfolios with the similar ex ante risk to a number of naïve 1/n strategies, to determine whether optimisation could improve return performance. Their results indicate that optimisation does outperform most naïve strategies and, based on asset allocations and time to retirement, it improves an investor’s accumulated wealth by 2- 30 percent.