Investment Fraud and Cognitive Biases: DIY Investor Protection

James W. Watkins, III, J.D., CFP®, AWMA®

CEO/Managing Member
InvestSense, LLC

With all of the investment options available today, many investors are intimidated, confused and frustrated by the investment process.  Recent studies also support the suggestion that many investors are perfect targets for investment fraud or already are victims of investment fraud. For instance,

  • A study by Schwab Institutional found that 75% of the investor portfolios studied were unsuitable for the investors given their financial situation and goals.1  Based upon my personal experience, I would put that number at approximately 90% based on issues involving inadequate, or “pseudo,” diversification;
  • A recent study by CEG Worldwide concluded that over 94% of those holding themselves out as wealth managers were more product salesman than wealth manager2;
  • Investment fraud is the number crime against the elderly, affecting an estimated 7.3 million older Americans, or one out of every five senior citizens3. Since that number only counts the instances of fraud actually reported, the number of victims is undoubtedly higher.

One of the problems with avoiding investment fraud is the difficulty in detecting some types of fraud due to the subtlety or complexity of the fraud itself.  Another problem with detecting fraud is the personal biases and beliefs that each investor has regarding investing.  The purpose of this article is to alert investors to some of the more common elements of investment fraud so that they can prevent unnecessary investment risk and financial loss due to investment fraud.

Investment Fraud and Cognitive Biases   
The common response to investment fraud is to call for greater investor education programs.  However, a recent law review article suggests that investor education programs may be largely ineffective due to cognitive issues such as cognitive biases and/or cognitive deficits of investors.  Cognitive biases are personal beliefs that impact our decisions.  Cognitive deficits are impairments in mental ability, including impairments due to aging.

In the article, “Deception, Decisions and Investor Education,” the author suggests a model of fraud victimization, which she refers to as the “deception/decision cycle.”4  As investors are provided with investment information, they filter the information through their personal beliefs, beliefs based upon a combination of actual experience, education and first impressions.

The beliefs, or biases, may or may not be accurate, but they become so ingrained, or “anchored,” within a person that the person resists any conflicting information.  These biases may be strengthened even further by what are known as “truth” and “authority” biases, a person’s tendency to accept a statement as true, especially when the statement comes from someone with actual or perceived authority or expertise.

The individual investor, whether because of issues such as cognitive biases/deficits, the complexity of the investment information, or the sheer volume of such information, then fails to recognize the deception involved in the fraud.  Barnard identifies other factors such as impulsive behavior and overconfidence that may contribute to the “deception/ decision cycle.”

Asset Allocation and Cognitive Biases      
A perfect example of how cognitive biases can negatively impact investment decisions is a common misconception involving asset allocation.  When you mention asset allocation or diversification to most investors, they think in terms of quantity rather than quality. Consequently, a large percentage of investors have portfolios that are diversified in terms of types and numbers of holdings within the portfolio, but the portfolios are not “effectively” diversified due to the high correlation of returns between the investments.

I like to refer to these portfolios as being “pseudo” diversified since they appear to be diversified, but they do not actually provide an investor with the benefits of a truly diversified portfolio. The high correlation between the investments results in an investor having less downside protection than they would have with a truly diversified portfolio.

As an example, most people would consider a portfolio consisting of a large cap fund, a small cap fund, an international equity fund and a bond fund to be diversified since it consists of four different types of funds.  A review of a correlation of returns matrix for a portfolio of four exchange traded funds (ETFs) representing the four categories over the time period 7/22/2013 to 2/20/2018 tells a different story.

IWB IWM EFA AGG
IWB 1.00 0.87 0.83 (0.19)
IWM 0.87 1.00 0.72 (0.20)
EFA 0.83 0.72 1.00 (0.13)
AGG (0.19) (0.20) (0.13) 1.00

IWB – Russell 1000 Index ETF (1)
IWM – Russell 2000 Index Fund ETF (2)
EFA – MSCI EAFE Index ETF (3)
AGG – Barclays Aggregate Bond Index ETF (4)

Analyzing rolling periods of returns often provides a better picture of trends. An analysis of three rolling five-year periods of returns for the referenced ETFs provides the following results:

1&2 1&3 1&4 2&3 2&4 3&4
2013-17 0.82 0.79 (0.04) 0.56 (0.20) 0.15
2012-16 0.85 0.82 (0.09) 0.65 (0.20) 0.05
2011-15 0.89 0.88 (0.13) 0.76 (0.18) (0.05)

The higher the matrix number, the higher the correlation of returns.  A negative matrix number indicates a negative correlation of returns, which means that the two investments behave differently during various market conditions.

The matrix shows a high correlation of returns between the large cap and the small cap ETFs, and a high, albeit varying, correlation of returns between the international ETF and the large and small cap ETFs. The matrix clearly shows a low correlation of returns between the bond ETF and the other three ETFs. The results are consistent with studies that have shown an increase in correlation of returns between equity-based investments over the past decade, especially during periods of increased volatility in the markets.5

The correlation of returns matrix exposes the false illusion of diversification created by the bias of assessing diversification on the quantity of funds or types of funds alone.  This bias is sometimes difficult to remove, as diversification based on quantity and type seems to make sense.  Unfortunately, that is exactly what some unethical financial advisers rely on, as they try to exploit the “truth” and “authority” biases as they recommend overpriced, underperforming and unsuitable investments to investors and investment fiduciaries, such as pension plan sponsors.

Portfolio Optimization and Cognitive Biases     
If you have had an asset allocation plan or portfolio optimization plan prepared by your financial adviser, look at the plan and see if there is anything in the plan that gives you the projected risk, return or correlation of return data on the actual investment portfolio the financial adviser recommended to you.  I have rarely seen such an analysis using the investor’s actual investments, primarily because the commercial asset allocation/portfolio optimization programs used by most financial advisers are not designed to produce such “real world” analyses.  And yet, the calculations can be done using Microsoft Excel.

In many cases this failure to provide a “real world” portfolio analysis results in recommendation-implementation gaps, often leaving investors with portfolios significantly different from the asset allocation/portfolio optimization plan provided to them by their financial adviser, especially with regard to exposure to unnecessary investment risk.

The calculations used in calculating the projected risk, return and correlation of returns statistics for an investor’s actual investment portfolio are complex.  Consequently, most investors are unable to calculate the actual portfolio’s statistics themselves or to otherwise detect an investment adviser’s fraudulent behavior.

Too often an investor falls prey to the “trust” bias or the “authority” bias and just accepts the plan given to them without questioning the accuracy of the plan or the failure to provide a “real world” analysis of the actual investment portfolio that their financial adviser recommended.  But you should question your financial adviser and ignore any “trust” or “authority” biases, especially since the portfolio optimizers often produce recommendations that are counter-intuitive or blatantly unsuitable.

The regulators take the basic position that anyone with an investment time horizon less than five years should generally avoid equity-based investments since they might not have enough time to recover any losses suffered in the market.  With the first calculator, we ran the same set of personal investment parameters, with the only exception being that we varied the risk tolerance level in each scenario.  The results are shown in Appendix A.

Two clear issues emerge regarding investor protection.  First, regardless of the investor’s risk tolerance level, the calculator consistently recommends a portfolio consisting of approximately 60% equities and 40% bonds/cash.  Second, the calculator completely ignores the “low” risk tolerance entry, exposing the risk averse investor to an undesired level of investment risk due to the recommended equity allocations.

With the second asset allocation calculator, information was requested on both the investor’s risk tolerance level and the investor’s investment time horizon.  Once again, we used the same set of personal investment parameters for each analysis, changing only the risk tolerance level and/or the investment time horizon.  The results are shown in Appendix B.

If you accept the regulators’ position regarding a minimum five-year investment time horizon for equity investments, then the second calculator’s equity allocation for the 3-5 year time horizon is questionable, as it recommends a 30% allocation to equities for the low risk investor and a 45% allocation to equities for a moderate risk investor.

When we expand the time horizon out to 5-10 years, the low risk investor get the same portfolio recommendations that the 3-5 year time horizon/moderate risk investor got, which obviously raises questions.   Strangely, the moderate risk investor with the 5-10 year time horizon receives a recommendation that increases the bond allocation to 65% and lowers the equity allocation to only 35%.

When we increase the investment time horizon to 10-20 years, we get basically the same recommendation for both the low risk and moderate risk investor, with the recommended equity allocation only varying by 5 percentage points.  The calculator appears to overweight the investment time horizon and basically ignore the low risk investor’s preference to avoid investment risk.

The last example is further evidence that most asset allocation/portfolio optimization software programs are highly unstable and susceptible to mistakes, so much so that they have been criticized as “estimation-error maximizers” by one industry expert.Investors who wish to protect their financial security would do well to replace any “truth” and/or “authority” biases with a healthy dose of skepticism and a willingness to question their financial advisers and/or their recommendations.

Investment Fees and Expenses and Cognitive Biases 
The next few paragraphs are going to get somewhat detailed. However, if you are like most groups that I have spoken to, you may experience an “aha” moment that will provide information you can use to protect your financial security.

Investors generally look to their financial advisers for advice and generally defer to any recommendations provided by their adviser.  Again, this is often the results of both the “truth” and the “authority” biases.  Many financial advisers limit their investment recommendations to actively managed investment products, which often are not in an investor’s best interests.

The negative impact of biases grows even deeper once we factor in the impact of fees and expenses.  Fees and expenses on index funds and ETFs are usually low since there is little or no active management of such investments.  Fees and expenses on actively managed mutual funds can vary, with some even assessing annual fees and expenses in excess of 1.0% per year.  Fees and expenses are important to investors since they reduce an investor’s end-return.

Assume that we have two funds, Fund A and Fund B, both with relatively similar performance returns.  Fund A is an index fund/ETF.  Fund B is an actively managed fund that has an R-squared rating of 93, which means that approximately 93% of Fund B’s return can be attributed to the performance of a benchmark index, in this case the index represented by Fund A.  However, Fund B’s annual fees and expenses are 1.0% per year, while those of Fund A are 0.25% per year.

Since most of the return of Fund B can be attributed to an index rather than the contributions of active management, why would an investor pay three times more in annual fees and expenses for Fund B?  Before investing in Fund B, it is useful to see just how beneficial the active management has been and exactly what the active management is effectively costing the investor.

One commonly used method for making such assessments is known as the Active Expense Ratio (AER).  The active expense ratio was introduced by Professor Ross Miller, a finance professor at the State University of New York at Albany.7  The AER compares a fund’s R-squared rating with the excess annual fees charged by the fund to determine a fund’s “effective” annual expense ratio.

There are those who argue that the active expense ratio is misleading.  However, when an actively managed fund derives most of its performance from an index and an investor can obtain that same index’s performance at a much lower cost, one has to question the wisdom of reducing one’s investment end-returns by paying “money for nothing” and reducing one’s end returns.  Why not save the unnecessary expense and put the money in the investor’s pocket? As the saying goes, “you get what you don’t pay for.”

And yet investors do it every day, impacted by “truth” and “authority” biases they may not even be aware of.  Some investors have no choice, as their company’s retirement plan may only offer actively managed, commissioned-based investment options as a result of their plan’s fiduciary being influenced by their own “truth” and “authority” biases.  Armed with the knowledge of both these biases and AERs, hopefully both plan participants and plan fiduciaries will act to provide more meaningful investment options within retirement plans.

Rex Sinquefield, co-founder of Dimensional Funds, summed up the issue of active management fees best:

We all know that active management fees are high. Poor performance does not come cheap. You have to pay dearly for it.

Investment Returns and Cognitive Biases
Investment advertisements and financial advisers may tell you that a certain fund had a certain return, but the figures are most likely misleading. Ads and advisers usually quote an investment’s returns in terms of the investment’s nominal returns. The problem with nominal returns is that they do not factor in any sales charges that an investment charges or the risk that an investment assumed in order to achieve such returns.

Load-adjusted returns reflect the impact that a front-end has on an investor’s end-returns. A front-end load is the sales charge that a mutual fund usually charges each time an investor purchases shares of the fund.

Investment theory states that return is relative to risk. Therefore, funds that assume greater risk should produce greater returns to compensate investors for such extra risks. Risk-adjusted returns factor in the risk a fund assumed and allow for a more accurate evaluation of a fund’s true performance.

The investment industry often likes to dismiss risk-adjusted returns with the statement that “investors cannot eat risk-adjusted returns. And yet, the investment industry has no problem using Morningstar’s “star” ratings to market their mutual funds. Interestingly, Morningstar uses a fund’s risk-adjusted return in determining a fund’s “star” rating.

The following table shows the significant impact that loads and risk can have on a fund’s relative performance. The funds shown here are retail, or “A,” shares of each fund. The returns reflect the five-year returns for each fund for the period ending June 30, 2018. The funds used for comparative purposes were:

  • American Funds Growth Fund of America (AGTHX)/Vanguard Growth Index Fund (VIGRX)
  • Wells Fargo Small Cap Growth Fund (EGWAX)/Vanguard Small Growth Index Fund (VISGX)
  • Fidelity Worldwide Fund (FWWFX)/Vanguard Global Equity Fund (VHGEX)
  • PIMCO Total Return Fund (PTTAX)/Vanguard Total Bond Fund (VBMFX)
Nominal Return Load Adjusted Return* Risk Adjusted Return Vanguard Risk Adjusted Return
AGTHX 15.47% 11.41% 12.88% 13.89%
EGWAX 11.40% 10.29% 8.00% 10.53%
FWWFX 11.36% 11.36% 9.15% 9.67%
PTTAX 2.10% 1.36% 1.16% 2.00%

* Load-adjusted returns courtesy of MarketWatch.com

As is generally the case with funds that charge front-end loads, the funds underperform comparable index funds that do not charge such fees. Mutual fund companies do not typically charge a sales charge, or front-end load, on retirement shares, the shares most commonly found in pension plans, such as 401(k) plans.

Wealth Management and Cognitive Biases           
“Anchoring” is one of the strongest cognitive biases and, with regard to investing and wealth management, one of the most potentially destructive influences on wealth preservation.  Anchoring can be defined as a reluctance to retreat from existing beliefs and decisions and a resistance to even consider new or opposing information.

The difficulty with addressing anchoring bias can be summed up with the observation from noted economist John Maynard Keynes that “the difficulty lies not so much in developing new ideas as in escaping from the old ones” and that “worldly wisdom teaches us that it is better for reputation to fail conventionally than to succeed unconventionally.”  Beliefs often become “truths,” regardless of whether such beliefs are valid, often resulting in unnecessary investment risk and financial loss.

A perfect example of the potential negative impact of anchoring can be seen in investors that adopt a buy-and-hold approach to wealth management, or, as buy-and-hold critics often refer to the strategy, the “buy, forget and regret” approach.  It is interesting to note that the buy-and hold approach to wealth management is apparently derived from an ongoing misinterpretation of a famous financial study.

A 1986 study, commonly known as the BHB study, concluded that approximately 94% of the variability of a portfolio’s returns was attributable to the portfolio’s asset allocation mix.The study made no representations whatsoever regarding the impact of asset allocation on a portfolio’s actual returns, only on the variability of a portfolio’s returns.

Nevertheless, financial advisers and investment companies misrepresent the study’s findings to support their buy-and-hold argument, claiming that all an investor has to do for investment success is to set up an appropriate initial asset allocation and maintain that allocation given the BHB study’s “findings.” The problem is that many investors have read or heard this mantra so often that they have fallen prey to the “truth” and “authority” biases and the misrepresentations are now firmly anchored into their personal beliefs.

It is interesting to note that the buy-and-hold approach is not derived from the works of the early pioneers of wealth management, Nobel laureates Dr. Harry Markowitz, the father of Modern Portfolio Theory, and Dr. William Sharpe.  In fact, Dr, Sharpe has recently stated that an “[i]nvestor’s asset allocation should change over time to reflect changing market values.”9 Asset allocation expert Roger Ibbotson has recently rebuffed the buy-and-hold strategy, stating that “[a]ctive management has about the same impact on performance as a fund’s specific asset allocation policy.”10

There are investment professionals who would argue that the buy-and-hold approach is fundamentally sound and is a prudent approach to investing.  These professionals usually claim that anything other than a buy-and-hold approach, with an occasional re-balancing to restore the original asset allocation parameters, constitutes market timing, which is both costly and ineffective.

From a legal perspective, what buy-and-hold advocates fail to realize is that the buy-and-hold approach completely ignores the proven cyclical nature of the market and the Prudent Investor Rule (Rule), whose guidelines are often used by regulatory bodies and the courts in determining questions of fraud and prudent fiduciary conduct.11 The Prudent Investor Act clearly states that a fiduciary should make changes in an investment portfolio when changes in the market or economy dictate such changes are necessary in order to protect the portfolio against unnecessary risk and losses.12  The Uniform Prudent Investor Act adds that “wasting beneficiaries’ money is  imprudent.13

The classic definition of market timing involves having all of one’s assets either completely in the market or completely out of the market.  The potential tax implications and the difficulty in perfectly timing the stock make such a strategy practically impossible.  However, re-allocating some of one’s resources to reduce investment risk exposure is not market timing, but smart, defensive investing.

Smart investors would do well to heed the advice of noted investor Benjamin Graham, who warned that “the essence of investment management is the management of risks, not the management of returns. Well managed portfolios start with this precept.”  Or, as noted by industry expert Charles Ellis, “the ultimate outcome of wealth management is determined by who can lose the fewest points, not by who can win the most14 Why? Simply because money lost in market downturns cannot fully participate in the eventual market recovery.

Various studies have documented the fact that avoiding losses has a much greater impact than missing potential returns. According to one recent study, missing the “best” 10, 20 and 100 days on the market, defined as the Dow Jones Industrial Average (“DJIA”), during the period 1990-2006 would have reduced an investor’s terminal wealth by 38%, 56.8% and 93.8% respectively.  Conversely, avoiding the worst 10, 20 and 100 days on the DJIA over the same period would have improved an investor’s terminal wealth by 70.1%, 140.6% and 1,619.1% respectively.15

Many investors suffered unnecessary investment losses during the recent 2000-2002 and 2008 bear markets due to their cognitive biases regarding the buy-and-hold approach to investing and their refusal to objectively consider defensive investment approaches. Unfortunately, these same investors will likely continue to suffer unnecessary investment losses unless and until they recognize their cognitive biases and objectively examine sound, defensive investment strategies.  As George Santayana pointed out, those who cannot remember the past are condemned to repeat it.”

The Active Management Value Ratio™ 3.0 and Cognitive Biases  
Arguably, the most effective way to attempt to overcome cognitive biases in investing is to study the standards established by the Rule. One of the key standards established by the Rule is that investments should be cost-efficient. The Rule states that actively managed mutual funds should only be recommended or purchased when “realistically evaluated return expectations….can reasonably be expected to compensate” an investor for the extra costs and risks associated with actively managed funds.16

When InvestSense performs a forensic analysis of the cost-efficiency of a pension plan or an investor’s portfolio, we rely on a proprietary metric, the Active Management Value Ratio™ 3.0 (AMVR).

The AMVR is based on the research of two legendary investment experts, Charles D. Ellis and Burton G. Malkiel. who found that

The incremental fees for an actively managed mutual fund relative to its incremental returns should always be compared to the fees of a comparable index fund relative to its returns When you do this, you’ll quickly see that the incremental fees for active management are really, really high-on average, over 100% of incremental returns. – Charles D. Ellis

Past performance is not helpful in predicting future returns. The two variables that do the best job in predicting future performance of [mutual funds] are expense ratios and turnover. – Burton G. Malkiel

The AMVR is simple to use, as it only requires the basic math, or “my dear Aunt Sally”  skills that we all learned in elementary school. All of the input data needed to calculate a fund’s AMVR score is available for free online at sites such as Morningstar, MarketWatch, Yahoo!Financial, and Fidelity Research.

For example, the slide shown indicates that the actively managed mutual fund in this analysis is not cost-efficient since:

  • the fund’s incremental expenses (277 basis points) far exceed the fund’s incremental return (93 basis points) using the fund’s AER. One basis point equals .01 percent of 1 percent.)
  • the fund’s incremental fees as a percentage of the fund’s total fee (81 and 98 percent) far exceed the incremental return provided for such fees (7 percent).

For more information about the AMVR and the calculation process, click here.

Conclusions
Investment fraud is a pervasive problem.  While various statistics are often cited as evidence of the problem, the truth is that such numbers are only a small percentage of the actual cases of investment fraud, as many cases go unreported and many victims of investment fraud are unaware that they are victims due to the subtlety or complexity of the fraud itself.

An emerging theory of investment fraud is that some investors are susceptible to investment fraud due to cognitive biases and/or cognitive deficits that impair their ability to properly analyze investment situations and the recommendations of their financial advisers.  It is imperative that investors become aware of and overcome potentially harmful personal biases, such as “truth” bias, “authority” bias and anchoring, in order to properly analyze investment options and better protect their financial security.

© Copyright 2018, InvestSense, LLC.  All rights reserved.

This article is for informational purposes only, and is neither designed nor intended to provide legal, investment, or other professional advice since such advice always requires consideration of individual circumstances.  If legal, investment, or other professional assistance is needed, the services of an attorney or other professional adviser should be sought

 Notes

1. Brooke Southall, “Wirehouse accounts don’t match client goals,” InvestmentNews, March 12, 2007, 12.
2.   Charles Paikert, “Poll: Few Advisers are ‘real’ wealth managers,” available on the Internet at www.investmentnews.com/article/20071029/FREE/710290324?template =printart.
3.   2010 IPT Elder Investor Fraud Survey, available online at www.investorprotection.org/learn/research/?fa=eiffeSurvey.
4.   Jayne W. Barnard, “Deceptions, Decisions and Investor Education,” Elder Law Journal, Vol. 17, No. 2 (2010), 201
5.   Ben Warwick, Searching for Alpha: The Quest for Exceptional Investment Performance, New York, NY: John Wiley and Sons, 2000), 101-120; Rachel Campbell, Kees Koedijk and Paul Kofman, “Increased Correlation in Bear Markets,” Financial Analysts Journal, Vol. 58, No. 1, (2002), 87-94
6.   Richard Michaud, Efficient Asset Management, (Boston, MA: Harvard Business School Press, 1998)
7.   Ross Miller, “Measuring the True Cost of Active Management by Mutual Funds,” Journal of Investment Management, Vol. 5, No. 1 (2007), 29-49.
8.   Gary P. Brinson, L. Randolph Hood and Gilbert L. Beebower, “Determinants of Portfolio Performance,” Financial Analysts Journal, Vol. 42, No. 4 (1986), 39-48.
9.   William F. Sharpe, Investors and Markets: Portfolio Choices, Asset Prices and Investment Advice (Princeton, NJ: Princeton University Press, 2006), 207-208; William F. Sharpe, “Adaptive Asset Allocation,” Financial Analysts Journal, Vol. 66, No.3 (2010), 45-49.
10.  Roger G. Ibbotson, “The Importance of Asset Allocation,” Financial Analysts Journal, Vol. 66, No.2 (2010), 18-20; James X. Xiong, Roger G. Ibbotson, Thomas M. Idzorek, Peng Chen, “The Equal Importance of Asset Allocation and Active Management,” Financial Analysts Journal, Vol. 66, No.2 (2010), 22-28.
11. Tibble v. Edison International, 135 S. Ct. 1823, 1828 (2015).
12. Restatement Third, Trusts § 90 (The Prudent Investor Rule), comment e(1), copyright 2007 by The American Law Institute. All excerpts from the Restatement herein are reprinted with permission. All rights reserved.
13. Uniform Prudent Investor Act, Section 7, introductory comment.
14. Charles Ellis, ”Loser’s Game,” Financial Analysts Journal, Vol. 31, No. 4, 19-26;
Charles Ellis, “Investment Policy: How To Win the Loser’s Game,” 5th Ed., (Chicago, IL: Irwin Professional Publishing, 2009), 81.
15. Javier Estrada, “Black Swans, Market Timing and the Dow,” available online at papers.ssrn.com/sol3/papers.cfm?abstract_id=1086300, 3-7.
16. Restatement (Third) Trusts, Section 90, comment h(2).