If you are like most people, your initial reaction to the question posed by the title to this white paper is “no.” However, for many investors, the answer is “yes.” 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 recent study by Schwab Institutional found that 75% of investor portfolios were unsuitable for investors given their financial situation and goals;
A recent study by CEG Worldwide concluded that over 94% of those holding themselves out as wealth managers were more product salesman than wealth manager;
The 2010 IPT Elder Investor Fraud Survey reported that investment fraud is the number crime against the elderly, affecting an estimated 7.3 million older Americans, or one out of every five senior citizens. 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 subtleness 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 investors can prevent unnecessary investment risk and financial loss due to investment fraud.
Fraud and Cognitive Biases
The common response to investment fraud is to call for greater investor education programs. However, a recent law review article in The Elder Law Journal 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.”1 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. An Investor’s beliefs, or biases, may or may not be accurate, but they can 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 of the sheer volume of such information, may fail to recognize the deception involved in the fraud.
Asset Allocation and Cognitive Biases
A perfect example of how cognitive biases can negatively impact investment decisions is a common misperception 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, or overlap, between the investments.
Portfolios that are not “effectively” diversified are sometimes referred to 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 (IWB – iShares Russell 100 Index), a small cap fund (IWM – i Shares Russell 2000 Index), an international equity fund (EFA – iShares MSCI EAFE Index) and a bond fund (AGG – iShares Barclay Aggregate Bond Index), to be diversified since it consists of four different types of funds. A review of a correlation of returns matrix for a portfolio of the four exchange traded funds (ETFs) representing the four categories over the time period 8/31/2003 to 8/31/2011 tells a different story.
IWB/IWM – 0.93 IWB/EFA – 0.91 IWB/AGG – 0.05
IWM/EFA – 0.81 IWM/EFA – (0.03) EFA/AGG – 0.11
Analyzing rolling periods of returns often provides a better picture of trends and the persistence of trends. An analysis of rolling five year periods of returns for the referenced ETFs provides the following information:
2010-06
IWB/IWM – 0.966 IWB/EFA – 0.970 IWB/AGG – (0.308)
IWM/EFA – 0.896 IWM/AGG – (0.325) EFA/AGG – (0.432)
2009-05
IWB/IWM – 0.985 IWB/EFA – 0.991 IWB/AGG – (0.282)
IWM/EFA – 0.977 IWM/AGG – (0.338) EFA/AGG – (0.340)
2008-04
IWB/IWM – 0.967 IWB/EFA – 0.999 IWB/AGG – (0.445)
IWM/EFA – 0.973 IWM/AGG – (0.518) EFA/AGG – (0.4650
The higher the matrix number, the higher the correlation of returns and performance. A negative matrix number indicates a negative correlation of returns, which means that the two investments behave differently during various market conditions.
The matrix clearly shows a high correlation of returns between the large cap and the small cap ETF, 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. An argument can be made that a portfolio consisting only of the large cap ETF (IWB) and the bond ETF (AGG) would produce similar results.
Since fees and expenses are relatively low for most ETFs, cost is not that much an issue with a portfolio of ETFs. Since many financial advisers do not use index funds or ETFs in making recommendations, the negative impact of “pseudo” diversification can be seen in a portfolio of load-based mutual funds, again representing the four asset categories used in the ETF portfolio. The mutual funds represented are American Funds Growth Fund of America (large cap equity), Oppenheimer Discovery (small cap equity), Fidelity Worldwide (international) and PIMCO Total Return (bond).
2010-06
Am/Opp – 0.922 Am/Fid – 0.981 Am/PIMCO – 0.705
Opp/Fid – 0.948 Opp/PIMCO – 0.688 Fid/PIMCO – 0.597
2009-05
Am/Opp – 0.922 Am/Fid – 0.981 Am/PIMCO – 0.519
Opp/Fid – 0.948 Opp/PIMCO – 0.636 Fid/PIMCO – 0.451
2008-04
Am/Opp – 0.893 Am/Fid – 0.989 Am/PIMCO – 0.052
Opp/Fid – 0.935 Opp/PIMCO – 0.482 Fid/PIMCO – 0.148
The data shows the correlation of returns over rolling five-year periods in order to show not only the correlation of returns, but also the trend in correlation of returns. Once again, we see the same high correlation of returns between the equity-based mutual funds, with a lower correlation of returns between the bond fund and the equity-based funds that we saw with the ETF portfolio. 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.
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 unscrupulous financial advisers are relying on, as they try to exploit the “truth” and “authority ” biases.
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. Investors rarely see 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 a “real world” analysis. 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 required to calculate 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 counterintuitive and/or contrary to existing legal standards.
Some examples may help to prove my point. Two of the most important factors in constructing a suitable investment portfolio are the investor’s risk tolerance level and the investor’s investment time horizon. With that in mind, an experiment with two popular online asset allocation calculators provides some interesting results.
The first asset allocation calculator asked about risk tolerance, but did not even ask about investment time horizon. 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 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 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, the same set of personal investment parameters are used in 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.
Expanding 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 45%.
Increasing the investment time horizon to 10-20 years produces 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 just 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 industry expert Richard Michaud. 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.
Investment Fees and Expenses and Cognitive Biases
Investors 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, commission-based products, which may not be in an investor’s best interests.
The negative impact of biases grows even deeper once the impact of fees and expenses is considered. 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 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. The active expense ratio was introduced by Professor Ross Miller, a finance professor at the State University of New York at Albany. Professor Miller basically compares a fund’s R-squared rating with the excess annual fees charged by the fund to determine a fund’s “effective” annual fees and expenses.
In our example, the active expense ratio calculates to an effective annual active expense ratio fee of 3.02% for the active management of the fund, a little over 200% higher than the stated fees and expenses. For the four mutual funds in our sample portfolio, the active expense ratios were as follows.
American Funds Growth
R-Squared – 98.34
Stated Expense Ratio – 0.69%
Active Expense Ratio – 4.44%
Oppenheimer Discovery
R-Squared – 93.43
Stated Expense Ratio – 1.34%
Active Expense Ratio – 4.63%
Fidelity Worldwide
R-Squared – 97.58
Stated Expense Ratio – 0.71%
Active Expense Ratio – 3.06%
PIMCO Total Return
R-Squared – 68.43
Stated Expense Ratio – 0.56%
Active Expense Ratio – 0.53%
There are those who may 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 returns by paying “money for nothing” and reducing one’s investment returns. Why pay three times more for essentially the same results?
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 active expense ratios, it would not be surprising to see both plan participants and plan fiduciaries act to provide more meaningful investment options within retirement 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 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 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 Brinson-Hood-Beebower (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 since the BHB study proved that asset allocation determines 94% of an investor’s returns. 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 investors should change their asset allocation in response to changes in market values. A recent study by asset allocation expert Roger Ibbotson has rebuffed the buy-and-hold strategy, stating that active management and asset allocation have about the same impact on a portfolio’s performance.
There are many investment professionals who would argue that the buy-and-hold approach is fundamentally sound and does not constitute investment fraud. These professionals usually claim that anything other than a buy-and-hold approach, with an occasional rebalancing 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 t the Prudent Investor Act, whose guidelines which are often used by regulatory bodies and the courts in determining questions of fraud and prudent fiduciary conduct. 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.
The classic definition of market timing involves having all of one’s assets either in the market or out of the market. The potential tax implications and the difficulty in perfectly timing the stock make such a strategy practically impossible. Reallocating some of one’s resources to reduce risk exposure is not market timing, but smart, defensive investing.
Smart investors would do well to heed the advice of noted investor Ben 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.” Various studies support Graham’s postion, with such studies documenting the fact that avoiding losses has a much greater impact than missing potential returns.
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 other 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 their investment strategy. As George Santayana pointed out, those who cannot remember the past are condemned to repeat it.”
Conclusion
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 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 2011, InvestSense, LLC. All rights reserved.
This article is for informational purposes only, and is not designed or 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. Jayne W. Barnard, “Deceptions, Decisions and Investor Education,” Elder Law Journal, Vol. 17, No. 2 (2010), 201.
APPENDIX A
Low Risk Portfolio
Investment Parameters > Age: 50 > Assets: $250,000 > Risk Tolerance: Low > Tax Bracket: 25% > Economic Outlook: Moderate > Income Needs: 4%
Recommended Allocation > Large Cap Equity – 23%, Midcap Equity – 13%, Small Cap Equity – 9%, Foreign Equity – 14%, Bonds – 23%, Municipal Bonds – 18%, Cash – 13%
Moderate Risk Portfolio
Investment Parameters > Age: 50 > Assets: $250,000 > Risk Tolerance: Moderate > Tax Bracket: 25% > Economic Outlook: Moderate > Income Needs: 4%
Recommended Allocation > Large Cap Equity – 21%, Midcap Equity – 14%, Small Cap Equity – 10%, Foreign Equity – 16%, Bonds – 26%, Municipal Bonds – 18%, Cash – 0%
High Risk Portfolio
Investment Parameters > Age: 50 > Assets: $250,000 > Risk Tolerance: High > Tax Bracket: 25% > Economic Outlook: Moderate > Income Needs: 4%
Recommended Allocation>Large Cap Equity – 20%, Midcap Equity – 16%, Small Cap Equity – 13%, Foreign Equity – 17%, Bonds – 24%, Municipal Bonds – 0%, Cash – 10%
APPENDIX B
3-5 Year Investment Time Horizon
Low Risk Tolerance: Bonds – 70%, Large Cap Equity – 15%, Small Cap Equity – 5%, Foreign Equity – 10%
Moderate Risk Tolerance: Bonds – 50%, Large Cap Equity – 25%, Small Cap Equity – 10%, Foreign Equity – 15%
High Risk Tolerance: Bonds – 60%, Large Cap Equity – 20%, Small Cap Equity – 10%, Foreign Equity – 10%
5-10 Year Investment Time Horizon
Low Risk Tolerance: Bonds – 50%, Large Cap Equity – 25%, Small Cap Equity – 10%, Foreign Equity – 15%
Moderate Risk Tolerance: Bonds – 65%, Large Cap Equity – 20%, Small Cap Equity – 5%, Foreign Equity – 10%
High Risk Tolerance: Bonds – 40%, Large Cap Equity – 30%, Small Cap Equity – ]15%, Foreign Equity – 15%
10-20 Year Investment Time Horizon
Low Risk Tolerance: Bonds – 30%, Large Cap Equity – 30%, Small Cap Equity – 20%, Foreign Equity – 20%
Moderate Risk Tolerance:Bonds – 25%, Large Cap Equity – 35%, Small Cap Equity – 20%, Foreign Equity – 20%
High Risk Tolerance: Bonds – 20%, Large Cap Equity – 40%, Small Cap Equity -20%, Foreign Equity – 20%
James W, Watkins, III is an attorney, a CFP® professional and an Accredited Wealth Management Adviser®. His areas of expertise include wealth preservation, asset protection, investment fraud and fiduciary law. He is CEO of InvestSense, LLC, a registered investment adviser firm located in Atlanta, Georgia. For additional articles and information, visit the company’s website, http://www.investsense.com. Mr. Watkins can be contacted at tawj3@yahoo.com, and followed on LinkedIn and on Twitter @InvestSense.