Over the last several years, one of the issues of greatest concern for several families as they frame their long-term investment strategies has been the risk that a single capital market outlook might no longer be appropriate. Though we have discussed this in this space a few times, a new dimension is emerging: risk management in a more complex environment and the need for a tool to conduct sophisticated scenario analysis.
More than three decades ago, Barra led the way in the creation of risk models designed for portfolio managers to look at securities in somewhat of a different light. In fact, in the early 1980s, Nick Potter, who was then the CEO of J.P. Morgan Investment Management, told me that, in his view, the main practical insight of modern portfolio theory (MPT) was to redefine a stock as a collection of portfolio risk and return attributes. His insight, which paralleled that of MPT with respect to asset classes, was that rather than looking at a stock as a piece of a particular business, one should look at it as a set of particular risk exposures, each of which had some expected return attached to it. Barra’s work effectively led the asset management industry, in general, and equity managers, in particular, to start thinking of common and industry risk factors. Over time, Barra’s work has been extended to the field of fixed income and, more recently, to balanced asset allocation issues.
While one may argue that this construct ostensibly fits very well within an institutional framework, which typically operates in an asset/liability analytical framework, it has been harder to apply it in the wealthy family and wealthy individual arena. The only inroad it has made has been with respect to tax-efficient equity investing. Strategies involving active tax management around some index base, indeed, almost always involve factor analysis to ensure that the portfolio has as modest factor exposure deviations as feasible. This is meant to ensure that the portfolio performs as closely as possible to the benchmark chosen, all the while being able to take advantage of random individual security price movements to capture and realize capital losses when they are available. Thus, it produces index-like returns, with little or no tax liability and the potential for hyper tax-efficiency, if it generates net losses that can be used to shelter gains realized elsewhere in the portfolio.
In a context where there was only one major capital market scenario, factor analysis might be viewed as an unnecessary complexity to seek to manage risk exposures. Thus the urgency to use that tool has been missing so far and families have been content to focus on a traditional asset-allocation policy mix—whether formulated around a traditional mean—variance optimization or through the use of a goals-based process. The advent of uncertainty in the capital market scenario is changing this. Indeed, in a world where the assumption is that the past must be a prelude for the future, risk can easily be assessed based on the assumption that the various components of risk will remain unchanged and interact with one another in a predictable manner. However, what if certain risk exposures might be rising that have not been terribly important in the past? What if the relationships that have prevailed in the past no longer seem valid or at least seem less valid than they used to be? What if one considers a systemic change so likely that one tries to evaluate the way in which such a change may affect portfolios?
The first step in that direction, though weak and significantly incomplete, is the increased use of scenario analyses. Indeed, one of the industry responses to the massive uncertainty caused by the crash of 2008 has been to evaluate portfolio outcomes using a variety of possible and different scenarios. This allowed families to get a better picture of what might happen in a different set of circumstances. The first incarnation of this process involved looking at what a portfolio might have done, if one wound back the clock to one or several prior shock(s), either in the U.S. or abroad. This certainly helped assuage a few fears. Yet, the obvious insight came forth: what if what people fear is not a repeat in terms of economic or market circumstances, but a repeat in terms of capital losses? This immediately set limits on the use of historically based scenarios.
The next logical step was to conceive scenarios where one would imagine a certain set of economic developments and postulate the likely reaction of markets to these developments. This turned out to be a lot more challenging an analysis to create and execute than expected; in large part, this was because there was precious little data as to how a few of the industry’s clients’ nightmares might actually materialize. In fact, I can vouch for the fact that I was quite frustrated when considering certain sets of scenarios: I saw that the sample one was considering was either not exhaustive in terms of a likely range of outcome or not internally consistent in the way the various scenarios were put together. Yet, did we have anything better to offer? Though the immediate answer to the question was not positive, one gradually became inevitable.
This is where it might be highly advisable to learn from the factor analysis work pioneered by Barra and others, although one might need to use a few simplifying assumptions. The need for simplifying assumptions arises from the obligation that any advisor has to ensure that clients are fully included in and a part of the process that leads to the analysis. The sole objective of the exercise is for one to find a process that allows a family or an individual to understand 1) the presence of certain fears or hopes, 2) the way these fears or hopes should logically be expected to impact capital markets, 3) the extent that those capital market developments might interact with portfolio exposures to produce specific outcomes in terms of capital gains or losses.
One relatively simple solution is to use the style analysis framework, where factor exposures are viewed as styles. Fundamentally, such an approach is no different from the statistical analysis underpinning the risk models created by Barra and others, but it accepts the notion that one does not need to define a set of factors covering the full waterfront. Rather, the factors must be viewed as and selected in function of their being understandable and relevant from the point of the investor, particularly if he or she is not a financial expert. A crucial challenge for financial advisors is to know when they are called to advise or when they are simply asked to translate capital market realities into client language and client fears into financial realities without doing more than offering some form of reality test. Thus, the challenge is twofold. First, consider a set of factors that are as collectively exhaustive and individually differentiated as possible. Second, identify proxy variables that will both fairly represent these factors and be intuitively understandable to individual investors.
Once this is done, it becomes possible for individual portfolios to be evaluated in terms of how they would react, if there were a shock applied to different factors, as a matter of initial analysis, and subsequently how that shock might reverberate across other factors. Note, however, that such reverberation would be expected to be minor, if the factors one has selected pass the test of being sufficiently independent! Yet, as the practical cynic might say, show us where there is real independence in the world!!!
Though a number of individuals or firms have been proceeding down this path, it is our hope that others might start to consider this problem and offer possible solutions or thoughts that might lead to solutions. It would indeed be a great topic for not one, but a series of learned articles, which we would be happy to consider for publication. One would naturally expect academic research to offer significant insights, probably but not necessarily building on the work already done in this general direction, though possibly not precisely applied to the idea offered here. One would also naturally expect a number of practitioners to offer their own thoughts on how this might be applied in practice and to suggest a few dead alleys that should be avoided. One is reminded of the perennial, but crucially important, advice: “I asked you what time it is; I did not ask you how to make a watch!”
The Summer 2011 issue of The Journal of Wealth Management is different from our “usual,” because it starts with an article that is longer than anything we have ever published. William Jennings, Stephen Horan, William Reichenstein, and I thought that it would be very useful to revisit the literature that has been published in the private wealth management sphere and chronicle major insights and findings across a number of important subdisciplines. Pointing as it does to key insights and important literary building blocks, it should help practitioners who may not have had the time to follow the full breadth of the research that has taken place on the topic about which we all are so passionate!
The next three articles deal with various aspects of the all-important focus on the bigger issues! With this article, Lisa Gray completes the sequence of three articles on family governance, bringing them together and showing how they work together to support the family’s optimal achievement of the goals it sets, whether those goals are investment, personal, or business related. Then, Hungjen Wang, Anil Suri, David Laster, and Himanshu Almadi propose an incremental step toward combining the insights of modern portfolio theory with some of the propensities documented in the literature on behavioral finance. Finally, Ashvin B. Chhabra, Ravindra Koneru, and Lex Zaharoff work to understand the impact of portfolio diversification on the ability of an investor to move up the wealth spectrum, postulating that upward wealth mobility is a major individual goal and concluding that wealth mobility is unlikely without the assumption of idiosyncratic risk.
The next two articles broadly focus on capital market issues from a tactical, rather than long-term or strategic investment, standpoint. Brian Dightman explores techniques for managing the world of information overload and how it can help meet the evolving challenges of wealth management. Laurence Booth, Bin Chang, Walid Hejazi, and Pauline Shum postulate that stock market performance has to be driven by the real side of the economy, and more specifically, economic growth and, thus, link productivity growth with stock market performance, showing that investing in high productivity growth industries over the long term generates returns in excess of the market, even after adjusting for risk.
Our final two pieces, as usual, explore or cover unusual areas, to help our readers expand their horizons. The first, by Javier Enrique Ayuso, Ezequiel Lipovetzky, and Edward Vergara, provides advisors with tools to identify when the inheritance and gift tax for the Province of Buenos Aires (PBA) might be relevant, assess its potential cost, and think creatively about how to minimize the impact of this new transaction cost for the succession of PBA assets. The final piece, by Jean Brunel, reviews Meir Statman’s book, What Investors Really Want: Discover What Drives Investor Behavior and Make Smarter Financial Decisions, concluding that casual and professional readers will benefit from reading it.
TOPICS: Wealth management, risk management, financial crises and financial market history, factor-based models
Jean L.P. Brunel
Editor
- © 2011 Pageant Media Ltd
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