The Institute for Innovation Development recently talked with Ron Surz, president and CEO of PPCA Inc, Target Date Solutions and Age Sage Roboadvisor—a series of FinTech companies designed to financially engineer solutions to what Ron sees as faulty practices in traditional investment analysis and portfolio management practices. Armed with an M.B.A. in finance, an M.S. in applied mathematics and a strong pension consulting background, he is hard at work disrupting traditional investment management thinking and practices to develop what he sees as post-modern portfolio theory/asset allocation optimizations for better investment outcomes.
Hortz: You have been very critical of and very busy in disrupting the traditional investment management process and investment analysis tools being used. What are some examples of the “one size fits all” mistakes that you feel has characterized the investment industry for the past three decades?
Surz: There’s a long list of entrenched faulty practices in investment consulting, but let’s start by reviewing three of them. At the top of the list is the failure to identify talent (real “alpha”) in active managers. So what’s wrong with decades old practices on investment manager analysis? The answer is very straightforward: indexes and peer groups are terrible barometers of success or failure.
Another failed practice is using the S&P500 as core in core-satellite investing. The S&P dilutes active managers by bringing in deadweight stocks that the active managers don’t like (because they don’t hold them). The S&P is an alpha killer. There is a better core. It’s the stuff in the middle in between value and growth. This version of core empowers active managers by completing them and getting out of their way
On a newer front, target date funds (TDFs) became main stream about 10 years ago with the passage of the Pension Protection Act of 2016. This Act anointed TDFs as a qualified default investment alternative (QDIA). Fund companies jumped on the opportunity as a way to package product and increase sales. TDFs now exceed $1.5 trillion. The BIG problem is that they are all way too risky at the target date, which is when people retire. In 2008 the average fund lost 30 percent, and they’ve become riskier since then. It’s a crime that could possibly be corrected by lawsuits in the next market correction.
Hortz: What made you decide to take upon yourself to become a financial engineer in addressing these concerns? What were your first steps and what did you learn through this early stage?
Surz: I think John F. Kennedy was paraphrasing someone else when he said “Some see things the way they are and ask why. I see things the way they should be and ask why not.” My first step was getting educated, earning two Masters degrees in math and finance. Then I went to work for the largest pension consulting firm in its day, A.G. Becker, where I learned the craft of consulting. I wrote the code for some of the first performance reports, and developed some of the first peer groups that are used to benchmark performance. In doing so, I observed the flaws and resolved to do better, but the industry doesn’t want better—not sure why.
I also became Becker’s senior VP in charge of asset allocation/investment policy studies where I consulted to $trillions in defined benefit assets. So when target date funds appeared on the horizon they were a perfect fit for my education and experience, so I designed a TDF glide path that is now patented and has been the glide path for the SMART TDF Index with a ten year track record starting in 2008. This “Safe Landing Glide Path” protects at the target date like no other TDF available.
Hortz: Why and how did you go about developing your own set of indices?
Surz: In the late 1980s, having started my own consulting firm, I wanted to provide style analysis, which was just starting to be used, but none of the existing indexes met the criteria that I wanted. In order to do style analyses the way I wanted, I needed indexes that were mutually exclusive (no stock in more than one index) and exhaustive (all stocks were classified). So I made up a 3 X 3 classification scheme: Value-Core-Growth X Large-Middle-Small. This scheme has subsequently been adopted by Morningstar and Research Affiliates. A few years ago I expanded the approach into the “Next Generation of Style Analysis” that I call “Style Scan.” It graphs every stock in a portfolio in style X-Y space