In the two years since Riskalyze launched its advisor product, it has grown at a remarkable pace.
From $44 billion in assets under management in February to $90 billion in AUM today, it has clearly proven its popularity among advisors.
And now, it has the research to prove its methodology really is worth all the fuss.
Riskalyze, the company that invented the Risk Number for financial advisors and their clients to help align risk preference with portfolio risk, has released a new white paper that independently reviews, via a team of academics, its approach to measuring an investor’s risk tolerance and how it is applied to an investor’s portfolio.
“We see this playing a big role not only in helping to validate that we got the methodology right but also one of the big advantages this gives us [is] this gives us access to some of the bleeding-edge stuff that is still in theory form and in the labs,” said Riskalyze CEO Aaron Klein during a visit to ThinkAdvisor’s New York office.
While the white paper was commissioned by the firm, Riskalyze was contractually prevented from influencing the opinions of the authors.
Knowing an investor’s risk preferences is crucial for an advisor, both as a way for an advisor to add value as the caretaker for the investor’s portfolio and as a way to improve on the investor’s decisions.
Riskalyze’s “Risk Number” runs on the idea that everybody has an amount of risk they can handle. So Riskalyze quantifies that and expresses it as a number from 1 to 99.
Riskalyze measures investor risk preferences through the Riskalyze questionnaire, which offers a series of 50-50 gambles representing portfolio choices.
The numbers used in the questionnaire are based on a range defined by three values: the investor’s current assets in the portfolio in question, a lower bound specified by the investor as a “disastrous” loss, and an upper bound specified by the investor as an amount he would be “content” with.
Riskalyze also allows advisors to score portfolios on the same risk number scale, using the Riskalyze metric to assess both risk tolerance and portfolio risk
“It makes it very simple to create alignment between what the client says they want and what they’re actually going to get,” Klein said.
“One of the questions we would get: Advisors would say, ‘I believe that this works. I use it with my clients. This seems to work really well. How do I know you guys have done the math right? How do I know that this is correct?’” Klein told Thinkadvisor.
The white paper affirms the need for a quantitative approach to risk assessment in order for its outcome to be applicable to a portfolio – and it also affirms Riskalyze’s method as a viable solution.
Noah Smith, assistant professor of finance at Stony Brook University and co-author of the report, called Riskalyze’s approach “extremely simple, and extremely specific.”
“It offers choices that are binary, using numbers that are familiar to investors. This allows precise estimation and minimizes the risk that an investor will make mistakes while taking the questionnaire,” Smith said in a statement. “In addition, the questions are highly relevant to the investor, an improvement on questionnaires in which choices are only percentage-based or completely inconsequential to the survey taker.”
The paper also makes a number of suggestions, some of which Riskalyze has already started to implement.
“There’s a lot of great input that this team is giving us,” Klein said, adding, “A lot of times it takes 15 years to get concepts out of academia and into products and I think we’re going to be able to accelerate that cycle and do that a lot faster.”
One of the suggested improvements that’s already been implemented is an update to Riskalyze’s model of expected returns from one-factor model to a four-factor model.
Smith explained the significance of this improvement during a visit to ThinkAdvisor’s office.
“There’s no such thing as a free lunch. To get returns you have to take risks,” Smith said. “Factor models say which kinds of risks will get you more return if you take on that risk.”
A one-factor model says that the only kind of risk that matters is market risk.
“In other words, the risk that you’ll get caught in a market crash,” Smith said. “Before 2000, that was what most people used.”
Meanwhile, a four-factor model will look at market risk, in addition to a value factor (sometimes value stocks outperform sometimes they underperform), a size factor (sometimes small stocks outperform sometimes they underperform), and a momentum factor (which measures how much stocks tend to overshoot).
Klein said the original one-factor model was a result of “philosophical choices that our team had made before.”
While Klein said Riskalyze didn’t see a “huge noticeable difference” in the outputs after the change was made, he believes it was still an important improvement to make.
“I don’t think we saw any massive difference in the results of what advisors were seeing after we made those changes. But, [they were] good best practices to be aligned with the right approach,” Klein said.
Smith also emphasized the importance of updating to a four-factor model of returns.
“It’s hard to notice, but adding the four-factor model will make a substantial difference.” Smith said. Adding, “In the bowels of the things, it is doing a better job.”
A competitor to Riskalyze is FinaMetrica, which sells advisors a “psychometric” risk questionnaire of its own.
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