DELIVERED VIA E-MAIL TO e-ORI@dol.gov

May 4, 2010 

Office of Regulations and Interpretations

Employee Benefit Security Administration

Room N-5655

U.S. Department of Labor

200 Constitution Avenue, NW

Washington, DC 20210

RE: 2010 Investment Advice Proposed Rule 

To Whom It May Concern: 

Fiduciary360 (fi360) appreciates the opportunity to comment on the proposed rules on the 

provision of investment advice to participants and beneficiaries of participant-directed individual 

account plans, which will implement the provisions of the statutory exemption set forth in 

sections 408(b)(14) and 408(g) of the Employee Retirement Income Security Act, as amended.

About fi360 

Fi360 offers a full circle approach to investment fiduciary education, practice management, and 

support. Our mission is to promote a culture of fiduciary responsibility and improve the decision 

making processes of investment fiduciaries, including investment advisers, managers, and 

stewards. With legally substantiated Practices as our foundation, 1 we offer training, tools, and 

resources in support of that mission. In particular, fi360 Tools provide research, analytical, and 

reporting services, and are designed to aid advisors who serve as or support investment 

fiduciaries. In addition, we manage the Accredited Investment Fiduciary® (AIF®) and 

Accredited Investment Fiduciary AnalystTM (AIFA®) designation programs.2

 1 Fi360 publishes the Prudent Practices for Investment Fiduciaries handbook series. The Practices in the 

handbooks are legally substantiated by the law firm of Reish & Reicher (formerly known as Reish Luftman Reicher 

& Cohen), and formally reviewed by the American Institute of Certified Public Accountants (AICPA). 

 Fi360 is also 

2 At present, there are over 3,700 active AIF and AIFA designees. AIF designees receive training that 

provides a unique comprehensive overview of fiduciary standards of excellence, asset allocation, preparation of 

investment policy statements, manager search and due diligence, performance measurement, and other related 

subjects. AIFA designee training builds on that foundation and prepares students to provide Fiduciary Assessments 

to institutions. 
Office of Regulations and Interpretations

May 4, 2010

Page 2

dedicated to providing the fiduciary community additional resources through our webinars, blog, 

annual conference, and general advocacy efforts. 

General Comments

Fi360 commends the Department of Labor on its efforts to minimize and, where possible, 

eliminate conflicts of interest that may arise when fiduciary advisers provide investment advice 

to participants and beneficiaries. In particular, we believe that the fee neutral requirements in the 

proposed rules will provide significant benefits to participants and beneficiaries by removing 

incentives for fiduciary advisers to favor certain investments. 

With regard to investment advice arrangements that use computer models, fi360 has provided 

answers below to the specific questions raised by the Department in its Notice published on 

March 2, 2010. In the process of answering those questions, however, we became concerned 

that the level of specificity required in the design of a computer model to manage conflicts of 

interest will limit the utility of the model and make it difficult and expensive to certify. 

Consequently, we question the practicality of the approach and submit that a better approach 

may be to restrict eligible investment advice arrangements to the fee neutral approach. We ask 

that the Department to carefully consider these implications of using computer models as it 

finalizes the regulations. 

Answers to Questions Regarding Computer Models 

Investment Theories

What investment theories are generally accepted for purposes of Section 2550.408g1(b)(4)(i)(A), and what investment practices are consistent with such theories?

A computer model used to formulate investment advice for participants of 401(k) and 

other participant directed retirement plans necessarily involves two calculation phases. 

The first is to establish an appropriate asset allocation for the participant. The second is to 

select the specific investments (generally mutual funds or exchange traded funds) that 

will be used to populate a portfolio consisting of the selected asset classes. 

With respect to asset allocation, one generally accepted investment theory stands out 

among all others for purposes of the computer model, that being modern portfolio theory 

(MPT). MPT can be summarized as the principle that diversification across asset classes 

is a prudent method of managing risk and return. 

A corollary to MPT is that reasonable estimates of risk, return, and correlation values for 

specific asset classes can be used to estimate an efficient frontier of possible portfolios 

composed of various mixes of these asset classes. Given an efficient frontier that 

represents the various portfolios that provide maximum available returns (Y-axis values) 

associated with the various market risk levels (X-axis values), it is possible to determine 
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May 4, 2010

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a hypothetically optimal portfolio that is expected to align with the risk tolerance of a 

particular investor. 

Practices that are consistent with MPT include the use of asset allocation tools such as 

mean-variance optimization, Monte Carlo simulation, and Resampled EfficiencyTM3

It is worth noting that there is a generally accepted investment theory that could be used 

as an alternative to MPT in the development of an appropriate asset allocation; namely, 

Arbitrage Pricing Theory (APT). However, it is much more difficult to apply APT in 

practice than MPT because APT presumes that there are many variables that will have a 

bearing on economic and market outcomes. There is no consensus on what variables are 

relevant and the values that should be assigned to weight the impact of those variables. 

Thus, although the logic of APT is generally accepted, there are no generally accepted 

variables and input values to allow APT to be applied to the provision of participant 

advice through a computer model, especially one that must be programmed to avoid the 

risk of manipulation when conflicts of interest exist. 

optimization. The utility of these tools depends upon the reasonableness and integrity of 

the three key input statistics: return, risk and correlation. As discussed in answers to other 

questions, these input statistics must be carefully considered because asset allocation 

outputs provided to participants as investment recommendations can be biased through 

the manipulation of these input values.

With respect to the selection of investments to populate the chosen asset classes, there is 

also one generally accepted investment theory that is overwhelmingly important, the 

efficient market hypothesis. There are three forms of the efficient market hypothesis 

(EMH). They relate to the level of efficiency presumed to exist in a particular market, 

where a market can generally be thought of as an asset class. The three forms of the EMH 

are strong, semi-strong, and weak. While the three forms are mutually exclusive within a 

market, it is generally accepted that some markets are more efficient than others. This is a 

potentially big problem when it comes to programming a computer model, as will be 

discussed in answers to subsequent questions.

The strong form of EMH presumes that all relevant past and current public and nonpublic information is reflected in the prices of the securities that are available in a 

particular market. Therefore, under the strong form, both fundamental and technical 

analysis of securities pricing are pointless. If markets are strongly efficient, investors 

should simply use index funds that are most representative of the asset classes that are 

optimal, given their particular risk tolerances. There is academic evidence to suggest that 

some markets (large capitalization, U.S. stocks, for example) are quite efficient, at least 

sufficiently efficient to make it difficult to recover the added cost of active management. 

Positive alpha (added return attributed to the ability of certain managers to identify 

 3 Resampled Efficiency is a trademark of New Frontier Advisors, LLC. (http://www.newfrontieradvisors.com) 
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May 4, 2010

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mispriced securities in the market) does not exist except as a fleeting aberration in a 

strongly efficient market.

The semi-strong form of EMH presumes that past and current public information is 

reflected in securities prices but not non-public information. This level of inefficiency 

opens the door to outperformance by managers who have a special talent for uncovering 

non-public information that can cause other investors to misjudge the true value of 

securities, i.e. fundamental analysis can be effective. By buying underpriced securities, 

selling overpriced securities and holding them until other market participants recognize 

their pricing mistakes, talented managers can earn extra return (alpha). 

The weak form of EMH presumes that neither current public nor non-public information 

is properly reflected in securities prices, which opens the door even wider for capable 

practitioners of fundamental analysis to realize excess returns and generate alpha. 

However, under the weak form of EMH, past public information is reflected in current 

prices; therefore, technical analysis would not be worthwhile. 

There is academic evidence to support the semi-strong form of EMH for most asset 

classes that could reasonably be expected to be included in most participant directed 

retirement plans. There is also some academic support for the weak form of EMH, 

especially for securities that trade in “thin” or less well developed markets. 

Practices that are consistent with EMH are those associated with sound and consistently 

applied due diligence processes to select individual investments. The weaker the form of 

market efficiency assumed, the more active management based upon fundamental 

analysis is justified and the greater the need for more robust due diligence criteria to be 

built into the computer model. This point will be elaborated upon in subsequent answers.

Should this regulation specify such theories and require their application?

MPT and EMH should be specified in the regulation. The fact that the computer model 

approach will generally be relied upon only in those circumstances when conflicts of 

interest exist means that there will need to be a high level of specificity about the theories 

and the practices that will be permitted. The number of potential opportunities for input 

and assumptions to be manipulated will expand exponentially with the number of theories 

and practices permitted to be used in the computer model. The components of the 

computer model will need to be specific in order to (a) assure that the processes used to 

formulate the asset allocation and investment selection recommendations are reasonable 

and (b) make certification of the computer model practical.
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Should the regulation dictate the bases for model parameters such as the probability 

distribution of future returns to asset classes or particular investments?

The regulation should specify safe harbor bases for model parameters, such as a normal 

probability distribution of future returns to asset classes or particular investments. 

However, the regulation should permit certain other bases if they are justified by 

objective evidence that they are effective, consistently applied and do not result in 

recommendations that systematically favor a service provider to the plan (i.e., cause a 

potential conflict of interest to be realized by a calculation methodology that is not 

specified as permissible under the regulation’s safe harbor provisions). For example, it 

should not be permitted for the computer model calculations to result in over-allocation 

to those asset classes or investments that involve proprietary funds of the investment 

service provider relative to what would have been recommended using safe harbor bases 

for model parameters. 

Should the regulation specify certain practices as required by generally accepted 

investment theories, or certain other practices as proscribed by such theories?

In order to assure the objectivity of the recommendations and to make certification of the 

computer model practical, certain practices should be specifically permitted as a safe 

harbor. For example, mean-variance and Resampled Efficiency optimization and Monte 

Carlo simulation should be specifically permitted to formulate asset allocation 

recommendations. Specific minimum due diligence criteria, however, should be 

proscribed for the selection of investments. Other practices may be permitted if they are 

justified by objective evidence that they are effective, consistently applied and do not 

result in recommendations that systematically favor a service provider to the plan. 

What are examples of investment theories that are not generally accepted? Should this 

regulation expressly proscribe the application of certain such theories?

Investment theories evolve based on academic research and practical experience; 

therefore, it is difficult to draw a sharp distinction between those that are accepted today 

and those that are not. Nevertheless, for purposes of this regulation, it would be advisable 

to state that recommendations generated from the computer model based upon technical 

analysis or market timing are not deemed to be based upon a generally accepted 

investment theory and are therefore not permitted. Technical analysis and market timing 

is not consistent with EMH. In addition, the task of evaluating and certifying a proposed 

computer model based upon technical analysis or a market timing strategy would be too 

subjective to be practical. 
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Historical Data

What historical data should be taken into account in determining a model’s expectation 

for future performance of asset classes and specific investment alternatives? Should the 

regulation specify minimum standards for the data, such as a minimum number of years 

of experience to be included in the data?

At least the past ten years of historical data for each asset class should be used in order to 

determine a model’s expectation for future performance. This will help ensure that the 

data will be based upon a full market cycle.

It is important to note that many asset allocation tools use forecasted risk-premium 

adjusted input data, rather than historical data. This adds a dimension of art to the science 

because the data is adjusted based upon some form of econometric modeling. It would be 

difficult, if not impossible, to anticipate all of the different factors that could or should be 

included in these forecasts; therefore, it would be necessary to either restrict the input 

values to historical data or to require the model builder to demonstrate the efficacy of 

using risk-premium adjusted input data.

Criteria and Bases for Asset Allocation

What types of criteria are appropriate and objective bases for asset allocation pursuant 

to proposed Section 2550.408g-1(b)(4)(i)(D)? Should this regulation expressly designate 

some criteria as appropriate and objective and/or other criteria as not appropriate or not 

objective? Should it do both, thereby establishing a list of criteria that models must 

consider to the exclusion of all others? For example, the regulation could provide that 

computer models must consider only the historical risks and returns of different asset 

classes as a whole, information about the participants, and the expenses and asset 

allocation of each investment option under the plan.

The existence of conflicts of interest in an Eligible Investment Advice Arrangement that 

relies upon a certified computer model argues in favor of having a relatively short list of 

asset classes that will be specifically permitted (e.g., no more than fifteen asset classes 

that are widely used in participant-directed plans and for which well recognized indexes 

exist). Moreover, investors tend to be overwhelmed when too many investment options 

are offered, leading them to make poor choices or to avoid participation in the plan 

altogether. Thus, a short list of asset classes will assist with reducing investor confusion 

and lack of participation. 

In addition, only asset classes for which there exist tradable index funds that closely track 

the benchmark indexes should be permitted (i.e., the R-squared value of the fund relative 

to the best fit index should be close to one). Investment providers that have proprietary 

funds in uncommon asset classes may be tempted to place these in retirement plans if 

they can capture a larger share of the investment assets by doing so. These specialty 

funds, however, often have higher risks than the more common asset classes. 
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The regulation should provide that computer models must use reasonable risk, return and 

correlation statistics as input data to the asset allocation component of the computer 

model (as elaborated upon above). It also should require information about the 

participants to be used to establish an expected risk tolerance and return requirement for 

each participant. Finally, the regulation should specify minimum due diligence criteria in 

order to minimize the opportunity for the investment service provider to manipulate the 

criteria in order to drive more assets towards proprietary or higher paying options of the 

service provider. With respect to due diligence criterion, fi360 offers a scoring system to 

weight due diligence criteria and provide an objective methodology to select investments. 

An explanation of the fi360 due diligence methodology is available at: 

http://www.fi360.com/fa/help/pdfs/methodology.pdf.

Is a fund’s past performance relative to the average for its asset class an appropriate 

criterion for allocating assets to the fund?

Yes, a fund’s past performance relative to the average for its asset class is an appropriate 

criterion for allocating assets to the fund; especially risk-adjusted returns. See the fi360 

due diligence methodology referenced above, available at: 

http://www.fi360.com/fa/help/pdfs/methodology.pdf.

Under what if any conditions would it be consistent with generally accepted investment 

theories and with consideration of fees pursuant to 2550.408g-1(b)(4)(i)(B) to 

recommend a fund with superior past performance over an alternative fund in the same 

asset class with average performance but lower fees? Should the regulation specify such 

conditions?

The fiduciary obligation is to select a service provider, including a fund manager, who is 

able to provide the subject services at a fair and reasonable expense. The decision must 

be based upon evidence collected through a sound, consistently applied due diligence 

process. That is what makes an objective scoring system like the one offered by fi360 so 

useful in demonstrating the procedural prudence of a due diligence process. Therefore, 

the regulation should describe the fiduciary requirement of procedural prudence and 

provide guidance in establishing a conforming due diligence process, including minimum 

criteria.

On what if any bases can a fund’s superior past performance be demonstrated to derive 

not from chance but from factors that are likely to persist and continue to affect 

performance in the future?

It is not possible to demonstrate with certainty that out-performance is derived through 

factors beyond chance. Nevertheless, it is consistent with generally accepted investment 

theories to accept that out-performance may exist under the semi-strong or weak forms of 

EMH. 
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Fees represent a known drag on performance. Active management represents a possible 

means of improving returns in markets that are not perfectly efficient. Therefore, due 

diligence criteria pertaining to both fees and historic performance should be considered, 

along with other factors that can reasonably be expected to have a bearing on the utility 

of adding a particular investment to the portfolio.

Should the use of a fund’s superior past performance as a criterion for allocating assets 

to the fund be conditioned on such demonstration?

Each criterion used in due diligence should be consistent with generally accepted 

investment theories and should be consistently applied. It is not practical, or even 

possible, to condition the use of each fund on proof positive that the particular fund in 

question achieved over-performance based upon manager skill. Rather, the performancerelated criterion should be based upon sound theory and appropriate thresholds that are 

consistent with what would be observed if the market is not strongly efficient and certain 

managers are able to exploit the inefficiencies. Frequent and reasonably consistent 

achievement of positive alpha does not guarantee that a particular fund will continue to 

outperform, but, in a less than perfectly efficient market, using a performance-related 

criterion like alpha can be justified so long as other sound and consistently applied 

criteria (such as those relating to fees) also are used.

How, if at all, should a model take into account investment management style? For 

example, all else equal, should a model ascribe different levels of risk to passively and 

actively managed investment options?

The model should not assign different levels of risk to passively versus actively managed 

investment options because this would be neither practical nor reliable. Passive investing 

involves, by definition, a market level of risk because it is designed to directly reflect the 

market. Active investing is designed to align with the best fit index of an asset class but 

depart from it to some extent in order to create an opportunity to beat the index. Thus, the 

active manager may assume more, the same, or less than the market level of risk 

depending upon how the manager chooses to depart from the index. Measures of riskadjusted returns, like alpha and the Sharpe ratio, allow appropriate comparisons among 

actively managed and passively managed options in the same asset class. Additionally, 

style drift can be used as selection and monitoring due diligence criteria to supplement 

performance-related criteria. 

By requiring appropriate minimum due diligence criteria in the regulation, it is not 

necessary to ascribe different risk levels to active versus passive investment styles. More 

accurate and flexible methods of considering differences in risk can be addressed in the 

regulation by specifying commonly used and well founded due diligence process 

requirements.
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Conclusion

We truly appreciate the opportunity to provide our views on these important issues. Please do not 

hesitate to contact me if you have any questions or would like additional information. 

Sincerely, 

Blaine F. Aikin

CEO