Archive for July, 2010

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Paradigm Shift

July 26, 2010

This is the start of a larger thesis that will be expanded upon as it becomes better defined:

I have recently noticed the increase in people asking my opinion about the market and market conditions. “What do you think it will do?” “Where should I go with my money?” “What should I buy?”  I am not proposing that this is in any way unusual. In fact it is the most common question asked informally of the advisor. Nor am I proposing that no one before has considered the importance of approaching each client and their background as unique. I am, however, taking it a step further by proposing that some credence should be given to the idea there is absolutely no similarity between one client and another and that our tendency to group clients based on generalizations and formulas for similar (but not identical) variables will limit the effectiveness of both the advisors relationship with the client and the investment results.  For example, we often categorize or formulate our approach with clients based on such things as: client age, sociological category (baby boomers, generation y, etc), family category (single, divorced, etc), financial history, job category, medical history, etc. This need is formed out of an erroneous contemporary scientific approach based on such things as: data ordering, compartmentalizing, ranking and hierarchical ordering, variable `likeness` selection and collecting, and other structured and formulaic ranking patterns, which in some way is based on a desire for efficiency, ease of understanding, ease of client education, and solution gathering. This can lead to errors, oversights, and missed opportunities, through over-generalization. In a way, advisors can start to think of each client and their needs as if they were in their own place in space and time; unaffected by each other and related only by the concept of the universe (money).  In other words, the universe is money and the client’s situation is one of the unlimited number of realities.

To expand on this further, it is assumed that the need for us to follow this scientific paradigm of forced ordering fails not only in our approach to the client, but fails the market as well. In this case we create false and arbitrary ordering of investment categories, data groups, and results.  This it is proposed, allows us to make decisions on products and asset allocations more heuristically, it comes at the cost of accuracy. Just as each client has different variables in the creation of his/her investment strategies, beliefs, and abilities, so to does each investment era have different variables and results in its creations. What we see from false paradigms is a dissonance felt in the market when actual data does not correspond to these expectations. The erosion of former truths (through factual data results which do not correspond to historical ‘norms) causes the uncertainty, hesitancy, and instability in the market that we see now.

The urge to place restrictions on the number of possible realities is a desire we currently accept. It helps us sort through the multitude of data and make informed decisions based on that data and its relationship with other variables affected by and on it. In an advisor-client relationship it is used to decide on a limited number of possible investment choices and allocations based on our experience with what we deem “similar” clients. This can be misleading and is not necessary. Each client can be seen as having an unlimited choice of investments based on their unique situation. We should not be creating sub-sets based on some arbitrary classification(s) between similar variables. In other words, and often used, one variable alone (i.e. baby boomer, which itself is based on a subjective range and not a definate variable) cannot be used to form a cojent theory of correlation when there are dozens dissimilar variables between our client and the “model client” to which the theory is based. True, it can be said that there are limitations to the efficient frontier based on this clients risk tolerance. If you follow this line of thinking you may find that over a large data set of individuals, a series of possible correlations may be ascertained. This is true especially if you are dealing with clients with similar variables (such as age, or job type, etc).  This may tempt you to draw theories based on those loose correlations. It is at this point that we should be cautious. Although it is safe to say that two clients at age 50 represent identical variables (‘age’), the data resulting from a comparison of one, or even each, cannot said to be relevant for a third party of identical age. Additionally, there would be the inclusion of additional variables (such as past/current debt, desires, risk tolerance, ability to bear risk, liquidity needs, family responsibilities, medical history, etc), which would further break down your ability to form larger theoretical bonds that apply more generally to the population group. Having said that, we too often latch on to one variable and apply the same investment strategy to other clients who exhibit that variable. For some reason we succumb to the human failing where efficiency begins to surpass accuracy. We somehow tune out other incongruous variables that should be addressed in the next unique individual.

Furthermore, and with thanks to Larry MacDonald (“Canadian Business Magazine”) and his article “Contrary View on Stocks (revised)” from July 23rd, 2010 we are made aware of John Authers book “The Fearful Rise of Markets.”  In short, this book states that investors should be cautious of considering equity as a long term guarantee. Although, it states, “stocks have earned an average 8%-10% over the past century or two (which is more than double the return on bonds),” he warns that this thought lead to a massive amount of money pouring into equity, which perhaps has inflated the prices and misrepresenting their true (and maybe lower value).

Additionally, and to quote MacDonald and Authers directly: “the historical era for which we have the most complete data involved a long period of peace and prosperity as the world recovered from two world wars, abandoned communism, and enjoyed many technological advances.” The advances in all these area lead, again, to large volumes of money pouring into these sectors and lead to what can be considered a positive area for equity growth that, he says, may not be repeated. He continues by stating that: “during the twentieth century, all but three countries outside the US had at least one period of at least 20 years in which equities failed to beat inflation.” Some developed countries had periods of about 50 years where equity failed to keep pace with inflation. These situations were affected negatively by the global situation while the US and Canada benefitted.

These are wise considerations, since it is unlikely that we will have a data set that is not affected by the very different pattern of economic and global situations prevalent today. In the least, he concludes, it is worth revaluating the idea that equities are a long run sure thing. It is an important question because it anticipates what we are seeing now in both the academic writings on the subject and in the market inteslf. We are beginning to question our investment decision making paradigms. The market is hesitant and it is being addressed in these types of books. We are questioning if we should continue to allocate the largest portion of our portfolios to equity. We are in an economic transition that has fewer and fewer variables in common with the era whose data we currently use for our decisions.  He is anticipating the same error in judgement we use in dealing with clients. To take his point further and to expand on the analogy: as long as we continue to form our investment paradigms and, hence, asset allocation decisions, on this historical data, which until now we have accepted as truth, we will not be prepared for variables unique to today’s economic climate.  Our similar variable in this case is equity and the socio-economic environment is our dissimilar variable. Just like two clients, even if they have the same single variable, there are other variables with do not make for a cohesive comparison. Certainly we cannot approach them with the same theory. As noted above by Authers, there are a dozen dissimilar variables in the two economic eras in which we are speaking. Like clients with two different backgrounds, it is false and inappropriate to take the same approach since it is unreasonable to assume it will yield the same result.

What should be the conclusion then? Should we try to avoid using too simple an approach with the client, for example, the age approach? I would say yes. There are too many opportunities for client servicing missed. We are specialists; after all, we need not be lazy. Even if you believe that the market already affects the true price of the investment this is your client servicing opportunity. Some advisors have the same allocations for all their clients and in the same percentages. I believe there are huge missed opportunities here.

Should everybody move into guaranteed return vehicles or short term money? For some people I would say yes. In this new (2010) economic climate, I may also say yes; or in the least maybe move to an aggressive Templeton model. In any event, we need time to allow the new data set to sort itself out.  In the mean time, and for the risk-takers, the risk-reward paradigm is still valuable and can be maintained and applied to the different (and ever increasing) investment vehicles available today.  The only caveat for investors and their advisors is that the return must be considered speculative and cannot be based on historical data. It can only be estimated (without guarantee of course) on more short term data sets from that vehicle alone, and can only be compared cautiously with any historical estimate for its overall asset category. We have already applied this thinking to the dozens of new investment products, which do not have historical data sets, and have been succesful.  Although these products have been unfortunately categorized as “speculative,” “speculative” does not always equate to actual results of the investment. It is labeled such only because it has no historical data which to support a valid conclusion. The investment becomes the victim of the whims of fickle investors (through the advice of their advisors) because they cannot maintain a hold rating without the support of the historical data that is, ironically, not necessarily relevant in the current climate. These products often cycle through a boom and bust phase purely out of the volume of money coming in and out as a result of this insecurity.  Its waivering is further inextricably linked to our false need to categorize the product in each stage of development. This, and often through consensus reports and individual product classifications, affects the inflow and outflow of money for often arbitrary reasons.

If we remove our need for a relevant historical data set, we therefore must accept a freer, more diligent, and objective, examination of the short term data for our products. We can compare it to the historical data set and we can compare it across sectors and types, but must be careful to draw any inferences on gain or loss without an understanding that there are other factors that may make any comparison erroneous.

Likewise, the choices of asset allocation for our clients should be unique to each individual and should be compared with other “similar” clients with great trepidation. More often than not we have arbitrarily created such categories to make our job, and the job of educating the client easier. This is the very essence of passive investment strategies: using generic theories based on historical data sets and risk-reward strategies to create hands-off packaged choices for specific targeted individuals and groups.  Although strategies of this type are created on the assumption of the arbitrariness of market pricing and the theory that you will have greater gains simply by reducing fees comparable with active investment strategies (which is not incorrect), they are formed from the assumptions of return characteristics (paradigms) that may not be accurate for our current economic and sociological climate. When the current climate interacts with those choices, the discordance in return expectations will be exacerbated and losses (in terms of the actual return vs the expected spread over the historical figures, which may be an incorrect assumption all along) will be heavy as money will be quickly withdrawn out of nothing more than panic. In fact, this is what we are seeing now. The market participants are confused. We do not trust our existing paradigm. It is shifting, but nobody is really sure where. As a result money is quick to flow in and out of the market on the simplest and most irrelevant data. We are searching for another data set to rely on.  Ironically, by the time we do, it too will be obsolete. In the mean time expect some quick in-and-out- mispricing and arbitrage opportunities or for the faint of heart find some value opportunities and live through the volatility of the sorting out period.

In the end, we may create identical asset allocations for two or more of our clients of similar age (or some other similar variable) but it should be coincidental. They may also produce similar return figures, but we must be smart not to blindly apply that strategy to our next client- there are likely other variables that you are missing.  In the past, there may be a spread of one type of equity (again, often erroneously ordered) over another type. There may have been a positive spread of equity over fixed-income investments from one period to another. None of this suggests anything other than a situational uniqueness for the period in question; and we must be hesitant to make this the basis with which we base all future investment decisions. In an era where we will be looking after the finances for many elderly people, a unique client service experience should be followed by care, caution, and diligence in selecting an investment portfolio for that unique individual.

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