Watching the Trends; Don’t Follow Them

October 4, 2018News, News Archive

Woodstock Quarterly Newsletter / Summer 2018

Why Woodstock Holds to the “Real” Fiduciary Standard

We like to watch trends. The fundamentals of the work done at Woodstock is not following trends, however, but following actual companies and how we expect their managements to respond to change with the “tools” they have within their companies to continue to produce profits. After doing that work, we like to point out why you, our clients, should be at Woodstock. We believe that you are best served here.

The trends in investment management theory may be starting to bend Woodstock’s way. Two recent articles in the financial press have pointed out that: (1) volatility is not risk and (2) that there are limitations to modern portfolio theory (“MPT”). We agree with the first author that one of the most important questions in investment is: what is risk?[1] The author pairs finance academics and traders, at least one of whom use volatility to assess how much they might lose in a short-term investment. “But if you have a long-term horizon, volatility is an opportunity.” An investor’s ability to take advantage of that opportunity, however, requires fortitude.

Second, after reviewing indexes, stock returns versus bonds, and what a stock represents, the second author points out that stock investors are buying into “actual businesses and would be better served by seeking to understand them.”[2] Under MPT, a stock’s return is related to its “factor exposures” and can be explained by them. Buying an index captures those exposures without the work of understanding the underlying companies. The author points out that this is “backwards”. The stocks do “well or poorly because the underlying businesses do well or poorly”. “After the fact, we can use stock returns to derive a set of factor returns.” The most important point that he and we believe is that the general, growing belief in MPT will create opportunities for those who persist in trying to understand companies and their business prospects.

Trust and the fiduciary standard are much in the financial news. The U.S. Department of Labor (DOL) and the Securities and Exchange Commission (SEC) are dueling over responsibility and definitions. The vast majority of the investment world (banks, insurance companies and broker/dealers) cannot make the profits they have become accustomed to with a real fiduciary standard. We expect the committee designing this “horse” to come up with a “camel”, as of old. There is no real constituency defending a real fiduciary standard, not even the law schools you might expect. It is interesting to note that the last law school, Suffolk University, to require a course in trust law, the origin of fiduciary responsibility, has now dropped the requirement. Woodstock, however, will keep to the real fiduciary standard. Under the fiduciary duty, an adviser must act in the best interests of its clients and not favor its own interests over those of its clients.[3] Our clients and owners expect it of us and we believe others, who are not now our clients, will appreciate that commitment in the future.

“Big data” may change everything. However, we have a warning from an analysis of the 2008 financial crisis. When large technology projects need to make sense of “volume, velocity and variety” there is an appropriate and valuable use for big data. But the use of data models, describing the “whats” but not the “whys” brought large banks to their knees in 2008. One author says “we shouldn’t feel inadequate because we rely on our animal traits like gut, intuition and bias”,[4] in contrast to “trusting what the data tell us before we fully understand why”. Is the self-driving car an appropriate use of big data in helping to solve a large, technology project or something else? A recent article described the artificial intelligence (AI) at the heart of autonomous driving systems as “brittle, opaque and shallow”.[5] “Brittle because it can’t carry over insights from one context to another, opaque because humans can’t evaluate its neuron-like tangle of connections, and shallow because it’s easy to fool.” On the other hand, we can believe that the companies involved are building a database large enough to overcome the brittleness and shallowness problems and that someone will figure out how to use artificial intelligence on itself to solve the opaqueness problem.

We know that you are the most valuable business development tool that we have. Your referral of a friend, colleague or family member to us is the most important way that we grow.

We thank you for your support and want you to know that we are dedicated to serving your best interest.

William H. Darling, Chairman & President Adrian G. Davies, Executive Vice President

[1]  WSJ, 4/30/18
[2]  Barrons, 4/13/18
[3]  IAA Newsletter August 2018 p.1
[4] WSJ, 7/2/13
[5] WSJ, 5/14/18