Thoughts on Portfolio Management – Part A

One of the things that Our Man has noticed from his years in and around the hedge fund industry is that ability to manage a portfolio and think about the risks embedded within it is one of the most undervalued skill sets in the industry. 

Thus, in a bid to help himself become a better portfolio manager, Our Man’s going to be jotting down some of his thoughts and observations over the coming months (perhaps years, who knows!).  The categorizations aren’t mutually exclusive, and given his Swiss Cheese of a brain it’s likely Our Man will forget things so don’t be surprised to find addendum’s to them as we wander down this path.


The Analyst-Portfolio Manager Gap
Given his non-traditional background, coupled with being an analyst in his day-job, and a PM in this night-job, Our Man ponders a lot on this subject.  In fairness, a primary portion of this divide stems from Our Man’s puritanical belief as to what a PM’s role; namely that it’s predominantly focused on understand and managing the risk in the portfolio, with the intent of generating an absolute return.  Clearly there are other definitions of the role (e.g. maximizing annual returns, beat a bench-mark, etc), which may lead others to not see such a gap.

Furthermore, portfolio management is also something on which there’s very little formal training; after all the path is generally start as an analyst, become a very good analyst, then eventually get portfolios to manage – but are the skills to be an analyst and to be a portfolio manager the same?  Our Man believes that while there’s certainly overlap, there are substantial differences; most notably, that an analyst can generally start by considering each position of his/hers in the portfolio as unique, whereas as a PM must consider all positions are being inter-related.  These are two very different starting points, which require very different mindsets and skills.

Yeah, but what does that all mean?
At an exceptionally simplified level good analyst’s job is to identify the key drivers (1-3, normally) behind a company’s performance, to do a lot of (often very dull) follow-up research to identify various potential paths of these drivers and the probabilities of these paths, and then model out the expected returns of these potential paths.   In reality of course, neither the potential paths nor the expected returns from them are simple discrete numbers but ever-changing. 

However, for the point of a simple illustration, let’s assume our analyst is infallible (i.e. the probabilities and expected returns are certain) and take a very simplified 1 driver with only 2 possible paths (A & B) scenarios that will play out definitively in 1 year.  Path A is very likely (let’s go with 75%, implying Path B has a 25% chance of occurring) and will lead to a good return (say 50%).  Path B is far less likely but the result would be a major decline in the stock (say -70%). 

Exp. Annual Return (Position) = Prob (A) * Exp. Annual Return (A) + Prob (B) * Exp. Annual Return (B)
In our case; Exp Return = 20% = (0.75 * 50%) + (0.25 * -70%)

Overall, as the calculation above shows, the expected return from this position would be 20%.  While Path B is potentially terrible, its relatively small probability only resulted in the idea becoming less attractive.  However, even considering this, the position has a potentially an attractive return and thus the analyst may well go to his PM to pitch the idea.  Given the infallibility of the analyst (sadly, in this instance only) and the attractive return, the PM should put the position into the portfolio, right?

Well no, not necessarily.  Why? 
Well, here is where Our Man sees the PM and Analyst paths diverge. 
In all likelihood Exp. Return (B)  figure more heavily into the PM’s decision than the analyst’s.  The reason is simple, rather than look at each position on a stand-alone basis, the PM should consider the portfolio (and all its underlying biases) as a whole.   The skill-set to do this is clearly different as it requires an understanding of the portfolio’s biases, both intended and unintended, as well as an understanding of how others might see the biases of the portfolio.

-  The intended biases are easily understood; at the simplest level, imagine the driver was Real Estate prices and prob (B) was the probability of falling real estate prices.  If the PM knew that there were numerous positions in the book that would suffer from falling real estate prices it may not be sensible to add the position to the book with that same risk.  i.e. we have enough of that risk, and are getting better bang for our buck elsewhere.
- The unintended biases are more complicated, even in our simple world.  Imagine a 2 company portfolio.  Company A is a US Copper Company and its major risk is a fall in global demand for copper.  Company B is a French Telecoms Equipment Company, and its major risk is that the 3G networks that it has contracts to supply base stations for may get built out more slowly.  These two companies don’t share any obvious intentional risks; they’re in different countries, industries, sectors, and copper/base stations are massively correlated.  Yes, but…the unintended bias may be that they’re both plays on the same underlying thing – e.g. the base station company’s major contract is to build out a network in China, who’re also the marginal buyer of copper.  Hence, the addition of the new position may well increase an existing bet on China’s growth.
- The importance of the view of others:  While the analyst may be 100% right on all of their analysis, if the market views the drivers as something different (e.g. are using the Copper company as a proxy for investing in China, rather than caring about copper’s supply/demand characteristics) then it stands to reason that the behavior of the stock price may bear no resemblance to the analyst’s expectations (i.e. people become less bullish on China, so sell the stock, even though demand for copper is increasing).

That’s genesis Our Man’s view that the starting points of the analyst and portfolio manager should be different and the need to think about and build portfolio management skills to complement analytic ones.  Some more thoughts on portfolio management, in the coming week…