I have had a number of discussions over the years with investment professionals, most of whom are in the brokerage community, who believe that the investment management process is straightforward. You just need to pick the right things: the right stocks, the right sectors, countries, themes, etc. The rest is just the “messy” business of implementation.
In practice, I have found that as a portfolio manager I only spent about one-third to one-half of my time figuring out my picks. All that other “messy” stuff, if improperly managed, can lead to distressing results. Some examples are:
- Our diagnostics show that our selection process worked, but why did we underperform?
- We got fired over a misunderstanding???
- I’d hate to tell you this but John the portfolio manager and Mary the trader are continuously at each others’ throats…
This is one in a series of posts on all that "messy" stuff: What do you do after you’ve made your picks I would emphasize that there is no one size fits all answer. Your mileage will vary.
Portfolio Construction: how much to buy and sell
If the selection process is about deciding on what to buy and sell, portfolio construction is about deciding on how much to buy and sell. I would break down this process into the following steps:
- Deciding on your benchmark
- Deciding on what your bets are: minimizing your un-intended bets and properly sizing your intended bets
Reading your client, or What's the Real benchmark?
Benchmarks can vary greatly from one client to another. Here are some sample answers of what you might get when you ask the client “what is the benchmark” (with translations in parentheses):
(1) We’ve given this question a lot of thought and have done very careful studies, your benchmark is ___. (The benchmark is the stated benchmark).
(2) Make me money. Just don’t lose any. (The benchmark is the better of cash or the market)
(3) We selected you/your firm because of its history of adding value; or we are committing funds to this asset class by diversifying our exposure between three managers. (The benchmark is some combination of the returns of your competitors and the stated benchmark.)
These are just some common examples. In my experience (1) is rare. One simple example of this would be an index fund. If it's an active mandate and the client has already done a lot of work, this may be a highly customized benchmark.
Individual investors give (2) as an answer a lot. It might also be the pension plan or deferred compensation plan of a small group of executives in a company. Ideally, you should build some sort of timing model to understand when the asset class or your selection process gets into trouble and minimize risk during those environments. If you don’t have a timing model, figure out how much tolerance for loss the client has and then position your benchmark between cash and the market. Translate your risk tolerance estimate into weights of the relative importance of these two components.
As an aside, my formulation of a benchmark as being the better return of X and Y is not exactly fair, but whoever said that life was fair?
The answer (3) is very typical of an institutional mandate. It is a sad truth in life but in general, only top-quartile managers get new assets and bottom-quartile get dropped. As an example of the importance of the competitor positions, during the 1990s most international equity managers were vastly underweight Japan compared to the EAFE index. As a result most managers handily outperformed the stated benchmark of EAFE as Japan had been a laggard during that period. It was therefore important to know the median manager weight in Japan was during that period for EAFE-mandate managers.
I also knew of one manager who picked two “smart” competitors, top performing managers in his asset class, and estimated these competitors’ exposures. He then pegged the benchmark and portfolio to the average macro exposure of these two competitors (see the sidebar entitled Reverse Engineering a Manager's Macro Exposure for an example of how to estimate competitor position weights).
In future posts I will address other issues such as risk models, portfolio optimization, minimizing trading costs, etc.