Earlier this month, a federal jury ruled against the founder of F-Squared Investments, Howard Present, in a case that was first brought to court almost two years ago. The firm, at one time, was the largest marketer of index products using exchange traded funds (ETFs).
The case was related to a proprietary algorithm that was developed and used both by F-Squared as well as licensed to other investment advisers. On the surface, this algorithm was a huge game changer: it analyzed price trend and volatility data to generate triggers on when to buy or sell investments in assorted market segments. The portfolios of exchange-traded funds were to be rebalanced every so often based on changes in the triggers, with the general performance published daily as an index.
The massive gains reported as a result of this algorithm made it easy for Present to market and resell the algorithm as F-Squared's flagship product. By the time the SEC lodged its complaint, the algorithm's indexes were the United States' largest ETF-based strategy. That amounted to approximately $28.5 billion of invested assets tracking the indexes, according to the SEC.
The algorithm, AlphaSector, itself was not an issue, but the way it was used and marketed was.
Back tested data is held to extremely strict advertising standards
As reported by Reuters, the SEC uncovered that the data used was applied to historical market data, which meant the performance touted was only hypothetical. F-Squared launched its index in 2008, claiming that its algorithm had been in use since April 2001. This was blatantly untrue: the algorithm wasn't finalized until late summer of 2008.
Additionally, the analyst who calculated the numbers made a mistake doing so, significantly inflating the performance that appeared in marketing materials.
The error was based on the hypothetical situation that purchases or sales took place one week earlier than they did in fact - and the end result was that the gain shown was 135 percent. As all triggers were happening with psychic premonition of purchases and sales (all hypothetical actions were taken one week earlier than they would have happened in real life), these gains were, of course, unlikely to occur for any real portfolios following the strategy.
With such phenomenal numbers, naturally, Present had little trouble licensing out the algorithm.
Present's own culpability was in being told of the error in late 2008, and doing nothing with the information he received. He did not investigate the possibility of an error further, and continued to profit from misleading information until his departure from F-Squared in November 2014.
Later revision of the data showed that the original, exceptional results were false. Accurately applied, the data showed a potential real gain of as much as 38 percent, making the error an increase of over 350 percent over the best case actual scenario.
While in this case, the wrong-doing seems obvious, there's more that can be taken from this than simply pointing fingers at someone who didn't realize something was too good to be true.
The issue is a more basic one: Howard Present did not follow the SEC guidelines on advertising rule compliance. You can learn more about the most recent issues highlighted just last month by clicking here, but a main risk alerted highlighted is that your firm must not be misleading in any marketing materials.
Even if there hadn't been an error in the calculations, Howard Present would still have been liable for publishing, circulating, and distributing advertisements and marketing information that was misleading. His data wasn't based on actual performance of the algorithm: it was back tested, hypothetical data.
Why Howard Present, and not F-Squared alone?
A reason for Howard Present being singled out for direct action above and beyond the settlement against F-Squared itself is due to his integral part in both creating the marketing materials as well as selecting the triggers for the algorithm itself. He directly chose the rules that adapted the algorithm's triggers into a model portfolio of ETFs. Using those rules, an analyst at F-squared then calculated hypothetical returns for the model portfolio going back to 2001.
Using this hypothetical data may have been acceptable if and only if he'd disclosed the source of his data as being hypothetical and back tested.
Disclaimers of this nature are often lengthy - and can be longer than the performance reporting data itself - which can make for "ugly" marketing materials. In the interest of sleek ads and legible PowerPoint presentations, the choice may have been intentionally made to keep disclosures out.
Regardless of the reason, marketing materials accompanied by robust disclosures are a much better option than paying millions in a settlement when the SEC comes calling.
The Ripple Effect: other advisers affected by this case
The actions of F-Squared and the subsequent case resulted in a series of actions against other advisers as well. The related actions were due primarily to a lack of due diligence being followed when the advisers recommended the product from F-Squared.
While many of the firms who had to settle with the SEC as a result of the findings related to F-Squared attempted to claim that they were victims themselves, the SEC did not accept that excuse. Instead, the agency took the stance that the advisory firms failed in their execution of due diligence in insuring their clients received accurate information.
What does that mean for you?
It means your business needs to take deliberate steps to ensure that what you are recommending is true and disclosed accurately.
It means you need to work closely with your compliance and legal team and external advisers to be confident that you are not failing to meet the duty of care to provide clients with accurate information.
It means your recordkeeping needs to be more than sufficient to substantiate any and all claims you make regarding your performance.
For more information, read through Michelle L. Jacko, Esq.'s article in Wolter's Kluwer: Investment Adviser Performance Marketing and Advertising - What You Need to Know.
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