Sunday, October 9, 2016

Searching for Confidence


If we were more confident, we would commit. The lack of confidence is what prevents us to committing to another person, a political view and an investment of time, effort, or money.  Animals as well as humans over-rely on our or others' memory as a guide for our next committed actions. The difference between humans and animals is that out of bitter experience we have been disappointed that in particular cases the past was not repeated exactly as believed.

To protect ourselves from disappointment we search for systematic ways to predict the future. Often not finding the magic formula, we rely on so-called "experts."

Another Lesson from "The Track"

While at the track after I concluded either I couldn't find the next winner or in my opinion the betting odds were too low to make a sound bet, I began a life-long exercise. I listened to those around me in their conversations as to why they thought a particular choice was the correct one. In an over-simplification, these views generally fell into two camps. The first very much focused on especially current information about various horses, jockeys, trainers, times of prior winners, and track conditions. The second camp used various numerical inputs such as past speed records for the race, the weight the horse was carrying, whether horses that were favorites that day were winning at the expected rate, etc, etc. This second group was slavishly following a systematic procedure or as it was known at the track, they had a system.

The post-race reactions after members of each camp that did not win was most instructive. First both blamed various "experts" for not producing winners for them. Those in the first camp restudied the information they had before the race to see what critical insight that they missed that they should apply to future races. The second camp’s followers rechecked their data for accuracy and if their math was correct they would begin the search for a new system and a new set of "experts."

The first camp were my first exposure to the arts of analysis. They searched the very present competitive conditions. The second group were in effect statisticians who believed the future could be determined from the numbers.

Years later I recognized that these two camps exist today in guessing which way various elections will go and what is the most successful way to manage money.


As a career securities analyst I have never seen a number from which I didn't want more information and data. However, I am not a card carrying member of the statistical clan. The reason I do not claim membership is that I do not think the numbers by themselves provide the answers that I need to generate confidence.

There are two other reasons that I don't wish to fit under the statistician label. The first is historical. In the era when the Dow Jones Industrial Average was being constructed, those hard working clerks in brokerage firms who produced recommendations for investors and whose main source of corporate information were the very thin reports published by companies. These clerks were unable to visit companies or third party sources and were called statisticians. My guess is that my Grandfather's firm had one or more. It was not until the era when Benjamin Graham was going beyond the ratio analyses of annual reports that the term securities analyst evolved.

The second reason I do not want to march under the statistician banner goes further back in history, but is equally important today. Another Benjamin, Benjamin Disraeli the Prime Minister of the United Kingdom in the 19th century is quoted (most often in the US by Mark Twain) as saying "Liars, Damn Liars, and Statisticians" were  the source of bad information and conclusions. I am afraid, particularly this remains true in the political world today. Part of this tarnished label attached to statisticians has to do with polling. Not only did the Brexit polling not capture the true intentions of those in Northern England but that it was followed in Colombia. There were three pre-referendum polls that showed that the no vote in Colombia was between 34 and 38%. The final vote was the "No" vote carried 50.2%. Again the issue has a geographic focus. Most of the No vote was largely rural, which is more difficult and expensive to gather. I am guessing many of the current US polls are similarly flawed.

One of the mistakes some British made is crediting the bookies with analytical inputs. A similar mistake, I believe, is being made on this side of the pond. The believers in the efficacy of these inputs, do not understand that both measures are similar to the pari-mutuel system at the racetracks where the odds are not judged mentally but are calculated by the amount of money bet. Further, my guess is that the northern English farmers and most Republicans in the US are not by nature gamblers, so the weight of money is not representative of the voters.

Turning to our investment world, those that believe in factor investing or other asset allocation dictates are essentially statisticians looking for their "system" as some of their brethren did at the track. Recently JP Morgan Asset Management published a 72 page   "Guide to the Markets®". An analysis of some of its data is as follows:

It has identified seven  major factors; including High Dividend Yield, Small Cap, Minimum Volatility, Cyclical Sectors, and  Momentum. The two best factor portfolios in 2015 were the last and next to last in the first nine months of this year.

Asset allocation funds may have many adherents, however since 2006 in a performance array of ten different types of Fixed Income funds on average they ranked fifth out of ten with two years in fourth place and three in sixth place.

In a similar selection of ten major asset classes from 2000, asset allocation returns were again in the middle on average, with the best in one year getting up to third place and five times in seventh place.

There is a problem with the statistical-only approach. When will the creators of the factors or asset classes recognize the changes in our dynamic markets? If those changes are perceived too late, much of the growth in value will not be achieved. For example, when the four largest global companies in terms of current market cap are recognized with appropriate weights they are all relatively young companies that are still in their first to third  generation of management.  The four are Apple, Alphabet (Google), Microsoft, and Amazon.

Analytical Approaches

A good analyst examines the past statistics to see what items are likely to be absent going forward and/or deserve a different weighting going forward because of a change of conditions. In projecting the future it is also wise to assume some level of intellectual or financial fraud as well as less than perfect executions of plans. In addition one should expect that technology will both help and hurt people's efforts. At one point, it was good analytical practice to calculate eventual scrap value from written off plant and equipment. Today it may actually cost a company to close down and get rid of plant and equipment without a tangible scrap value. In today's fast moving world useful lives may be shorter than the depreciation schedules.

Beyond the analysis of the past what can the analyst use to project the future? To an important extent demographics is destiny. However, the raw numbers have to be modified by changes in social structure and education. The answers may be quite different from work force and consumer market applications. These trends are not just national but global in implications. In turn this suggests that any US investor that does not have approximately half of his or her earnings coming from beyond our borders is not appropriately hedged. However, we already live in a global world where almost every company large or small is benefiting or suffering from multi-national influences. Thus no matter where you pay your taxes, locally based multi-nationals are diversifying the national sources of your investment income without your instruction.

Investment Implications

One of the lessons from the racetrack is that short races are more difficult to get right. The first one out of the gate has a tremendous advantage over the slightly slower. In investing I have noted a similar phenomenon. Catching up is difficult. Thus, at the track and in terms of portfolio management I prefer the longer races where there is time to recover. Therefore, at this point in our history I would like to focus a couple years after the next series of US elections which may not end until 2019. At that point demographics from today's level and mix will be playing out. There will be some major technological changes, hopefully positive.

I am more confident in the run up to my preferred investment horizon, I will rely on the past pattern of periodic and relatively painful declines followed by much longer periods of gains which in total produce a reasonable rate of return for those who are in for the long-term. This philosophy will work until it becomes dangerous because of “fellow travelers’ enthusiasm.”   

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