Our principles and process are based on what we believe to be the most precise and accurate methods available to lead you to financial success. We will define financial success as making your assets last as long as you need them to, and then longer.
“In all affairs it's a healthy thing now and then to hang a question mark on the things you have long taken for granted.”
“The fundamental cause of the trouble in the modern world today is that the stupid are cocksure while the intelligent are full of doubt.”
“I think nobody should be certain of anything. If you’re certain, you’re certainly wrong because nothing deserves certainty. So, one ought to hold all one’s beliefs with a certain element of doubt, and one ought to be able to act vigorously in spite of the doubt. … One has in practical life to act upon probabilities, and what I should look to philosophy to do is to encourage people to act with vigor without complete certainty.”
—Bertrand Russell.
The sky is not blue, and the Earth is not round. Two statements that may raise an eyebrow in this day of heightened vigilance about misinformation. Bertrand Russell lamented over seventy years ago that our system for teaching young people was not instilling them with the ability to separate fact from opinion. He said, “Education ought to foster the wish for truth, not the conviction that some particular creed is the truth.” He also told us that to believe something, we need to have some sort of reason to expect that thing to be true. Truth is not the default, doubt is. But what is truth, and how do we navigate the current scorn of skepticism by those wishing for us to accept narrative as fact? Our intention is to examine the evolution of a key dogmatic principle of finance through the lens of critical thinking. I understand that the following description is a challenging read, it may take effort to find the relevance, and it is boring. Bertrand also told us that most people acquiesce to popular opinion because thinking differently and rigorously is hard. Our commitment is to do the hard things because they lead us closer to truth, even though we may never really attain it.
We find ourselves inundated by expert opinions regarded as facts, as some look with distaste at those foolish enough to think themselves wiser than those paid handily to formulate opinions masqueraded as certainties. We outsource our thinking and suspend common sense because people declared smarter than us in certain areas have borrowed good money to be stamped by universities as qualified to opine on esoteric matters. We quote studies we have never read, much less understood, and pay homage to unseen and unnamed experts who must be right because they purport to follow the rules of science. Perhaps I am a little old fashioned in my paradigm wherein science is the method by which we attack hypotheses until proven true, not assume them to be true until proven false. There is great danger in surrendering blindly your agency in decision making.
The genesis of truth came from Aristotle who defined truth thusly: “To say of what is that it is not, or of what is not that it is, is false, while to say of what is that it is, and of what is not that it is not, is true”. Seems easy enough, either a thing is or is not. Unfortunately, we have discovered tools that are not yet fully domesticated in both the areas of statistics and communications, and instead of the black and white consistency of “true or false” we have cascaded into the grey world of “likely and unlikely” without updating the lexicon of our expectations. We use statistics and algorithms to form narratives that rely on emotion to propagate. We find kernels of truth and build fabrications of certainty around shaky propositions that do not stand on their own. We are too easy to surrender our acceptance to things that are difficult to understand. Confidence does not equal competence. It is especially important to question those who are certain. They are the most likely to be missing something.
It is not within my realm of confidence or competence to preach to you what things are true and what things are false. That is up to the reader to decide. I would, however, like to share with you how we evaluate the world to facilitate good decision making. It is a misconception to believe that all good decisions are made based on fact vs fiction. Take the following premise: “technology stocks are going to go down”, a statement we hinted at in October, 2021. While this appears to be a bold prediction about future events, the mechanics of nature will conspire to make this statement alternatively true and false, sometimes simultaneously. When? To what extent? For what duration? Permanently or indefinitely? All follow-up questions that would be much more difficult for the fortune teller to surmise. We need to question predictions to ensure that we properly understand what things are being predicted.
As individuals, we build systems to analyze information over our lifetimes. Whether it be which plants will not take over the yard, or how many ants in the kitchen require professional assistance, we keep a close eye on our environment, and we act when we feel it is the best moment. Most of what we do is based on what we consider fact. When deciding the right poison for mulberries or ants we look to experts to show us the way. If only an expert on finance could be as right as an expert on killing ants. While we may never reach the base granularity of any topic, we at minimum need to make sure that logical consistency is not violated when accepting conclusions. In order to evaluate the structure of a premise, we need to have a system for gathering knowledge. We should all be experts in logic so that we can evaluate the composition of an argument.
Immanuel Kant broke truth into 3 different qualities, and modern publishers have been kind enough to continue printing three volumes of Kant’s tome on truth. But the real delineation is separating reason from judgement. We can reason with facts all day long, but the reality is that reason only tells you about the past and the present. You must use judgement to make decisions about the future because there is no determinism at our scale. There is too much bickering back and forth about what the future will bring, and not enough contemplation about what the future may bring and the consequences and probabilities of different outcomes. A yet undetermined outcome need never be argued over. The only considerations that matter are what happens if the outcome is as expected, or more importantly, unexpected.
We can gather knowledge through either reason or experience. The rationalists argued that all knowledge is discovered by reason. They posited that there is objective truth in our Universe and the mind can grasp this truth directly. They believed that knowledge is innate to the mind and that intuition can guide us. Mathematics is their key to the truth, and they believe that certainty is attainable. The empiricists disagreed and countered that all knowledge is found in experience. Only our senses can lead us to the truth. There is no reliable intuition on matters of which we have no previous experience. Experimental science is their preferred method for testing knowledge. Certainty is not attainable. Kant believed that there was a compromise when he said, “Thoughts without contents are empty, perceptions without conceptions are blind…. Understanding can perceive nothing; the senses can think nothing. Knowledge arises only from their united action.”
There could be a valid accusation of navel-gazing upon reading the above summary. An important distinction needs to be made between “that which contributes to good decision making”, and “that which leads to more consistent and predictable outcomes through good decisions”. Mastery exists in nuance. It is why experience matters. A textbook full of formulas can provide you with tools for solving problems, but it is experience that teaches you which problem you are facing. It is one thing to know that price volatility is a feature of equity investing, it is quite another to sit across the table from a person who is genuinely distraught that her account is worth 80% of what it was 6 months ago on paper. This is why we must unify reason and experience when making decisions. Charlie Munger once said, “Young men know the rules, old men know the exceptions”.
In the movie “Good Will Hunting”, Will (Matt Damon) is a disadvantaged young genius struggling with poverty, family problems, domestic abuse, and detachment issues. Sean (Robin Williams) is a psychologist appointed by the court to provide treatment to Will in lieu of jail. In a very instructive scene, Sean vividly breaks down for Will the importance of nuance and experience, and the difference between rationalism and empiricism:
“So, if I asked you about art, you'd probably give me the skinny on every art book ever written. Michelangelo, you know a lot about him. Life's work, political aspirations, him and the pope, sexual orientations, the whole works, right? But I'll bet you can't tell me what it smells like in the Sistine Chapel. You've never actually stood there and looked up at that beautiful ceiling; seen that. If I ask you about women, you'd probably give me a syllabus about your personal favorites. You may have even been laid a few times. But you can't tell me what it feels like to wake up next to a woman and feel truly happy. You're a tough kid. And I'd ask you about war, you'd probably throw Shakespeare at me, right, "once more unto the breach dear friends." But you've never been near one. You've never held your best friend's head in your lap, watch him gasp his last breath looking to you for help. I'd ask you about love, you'd probably quote me a sonnet. But you've never looked at a woman and been totally vulnerable. Known someone that could level you with her eyes, feeling like God put an angel on earth just for you. Who could rescue you from the depths of hell. And you wouldn't know what it's like to be her angel, to have that love for her, be there forever, through anything, through cancer. And you wouldn't know about sleeping sitting up in the hospital room for two months, holding her hand, because the doctors could see in your eyes, that the terms "visiting hours" don't apply to you. You don't know about real loss, 'cause it only occurs when you've loved something more than you love yourself.”
Our contention lies in agreement with Kant. Reason and experience are equally important, but in different ways. Reason is a set of tools that allow you to repeat solutions to problems that we encounter. You can find a lot of these on the internet. There is nothing more dangerous than a reasonably intelligent person with a cough and access to WebMD. Equal importance does not imply that they are equally easy to acquire. Experience requires time, effort, repetition, and in some cases pain. We know not to touch a hot stove because we burned our hand. A similar reaction can occur when learning not to write “naked call options”* or use excessive leverage in a portfolio, even if the textbooks explain thoroughly how to implement these strategies. Unfortunately, many portfolio managers only eventually learn the consequences of these dangers through third degree burns to other people’s money.
We have established a framework for what is truth and what is not truth and have defined the tools for expanding our knowledge. Now we need to synthesize these concepts into a framework for testing decisions. Decision Theory is a branch of Probability Theory that attempts to build models for making decisions. There are three types of Decision Theory: Normative, Prescriptive and Descriptive.
Normative Decision Theory attempts to identify optimal choices. It assumes the choices available to a semi-omniscient being who knows all future probabilities and numerical consequences of each option. Our transcendent subject does not know future outcomes, only their associated chances and payoffs.
Prescriptive Decision Theory attempts to observe behavior and develop a conceptual framework to help people make better future decisions. It uses a usefulness criterion as opposed to the correctness criterion of normative decision making.
Descriptive Decision Theory attempts to identify how individuals actually make decisions. It uses an empirical validity criterion.
The importance of identifying these differences in taxonomy lies in evaluating the assumptions used to create the tools available in our reason toolbox. Around the office we like to ask the question “Why use math when common sense will do?” I like to pair this inquiry with a neologism based on another well-known colloquial axiom “to the man with a hammer all the world is a nail”, we rephrase this “to a person with a formula, all the world is a math problem”. Einstein told us “Not everything that can be counted counts and not everything that counts can be counted”. Can we really trust theories and formulas created under a normative framework that assumes totally rational experts with perfect information? We think this is unwise. Just because a certain strategy is mathematically correct when perfect inputs are available does not make it likely that random inputs will lead to similar success. Furthermore, it seems unlikely that a model based on this criterion satisfies our definition of truth.
Harry Markowitz wrote Portfolio Selection as a guide to help us make decisions under uncertainty using “Rational Man” as a model. “The Rational Man” writes Markowitz, “like the unicorn, does not exist. An attempt to see general principles by which he would act, however, can be suggestive for our own actions”. Remember that normative analysis assumes future probabilities and payoffs are known, and that only the outcome is unknown. Markowitz continues, “The theory of rational behavior is not a substitute for human judgement. There is no integrated theory by which we could dispense with human beings if we had a sufficiently large and fast computer. The study of rational behavior has produced only general principles to be kept in mind as guides. Even the significance of some of these principles is subject to controversy”, here is the important part, “The value of the study of rational behavior is that it supplies us with a new viewpoint on problems of criteria—a viewpoint to be added to commons sense to serve as a basis of good judgement.”
Remember that Rational Man has access to all future probabilities and monetary consequences, but on the same page as the above disclosures, with which we agree, Markowitz tells us, “Problems concerning the proper information to serve as the basic inputs concerning securities are outside the scope of this monograph. There are no magic formulas to supplant the sources of information and the rules of judgement of the security analyst.” In other words, let’s just assume the inputs are right and develop a pretty formula that rational man would use if he had such information. Information which we are not even going to discuss how to gather. Smart people will figure out how to properly calculate capital markets expectations later. Well, we are still waiting. Most large financial firms annually publish their list of Capital Markets expectations, the basic inputs required to use Harry’s formulas. They are widely varied in both kind and degree. No two sets are identical. If we were truly dealing in fact, we would expect these calculations to be similar.
In the early evolution of finance, expected return maximization was the driving force used to make decisions. This was derived from the correspondence between Pascal and Fermat in the 17th Century, who were attempting to develop a system for making correct gambling decisions. They invented probability theory to determine what the expected payoff would be from a given decision. For instance, if a fair coin is tossed with an equal probability of heads and tails on a $1 bet, the expected return would be $.50. If another player was willing to sell you this bet for $.49, you should take it all day long. There are two main problems with expected return maximization: 1) it does not take the chance of ruin into consideration, if you only had $.49 a loss would leave you broke; 2) it does not consider the diminishing returns in relation to existing wealth. The answer to these issues was found by shifting to expected utility maximization.
The journey from utilizing expected returns maximization to expected utility maximization began when Daniel Bernoulli wrote a solution to the St Petersburg Paradox in the 18th Century, which was formulated by his cousin Nicolaus Bernoulli. The St. Petersburg Paradox involves a game of flipping a coin that continues to double the payout as long as the flip is heads. Once tails is shown the player receives the total accumulation up to the last heads. For instance, if the payout is $2, and heads is flipped three times with tails on the fourth flip, the player will receive $8. If one uses expected return maximization to calculate the buy-in for the game the answer is infinity. Bernoulli said of this, “The determination of the value of an item must not be based on the price, but rather on the utility it yields ... There is no doubt that a gain of one thousand ducats is more significant to the pauper than to a rich man though both gain the same amount.” He then used his proposed formula for utility maximization to calculate the maximum buy-in per level of wealth using a square root function describing the diminishing marginal utility.
Expected utility maximization substitutes “utility” for “returns” in the probability calculation of the expected outcome. Utility is subjective and attempts to measure the pleasure received from a certain result. For instance, when deciding between a stock and a bond, instead of simply calculating the expected returns, a rational man using EUM would calculate the pleasure received from the expected returns after adjusting for the risk involved. In other words, a lower, safer return would be preferred by a conservative investor, whereas an aggressive investor may take on more risk in exchange for a higher return. There is no standard measure of utility, and it is different for each person. Modern Portfolio theory assumes that rational individuals build portfolios expected to maximize their utility by giving the highest expected return for a given amount of volatility based on probability theory.
Markowitz explicitly used the Expected Utility Maxim as a foundation for Modern Portfolio Theory. He gives a very detailed synopsis of EUM in Part IV of Portfolio Selection, chapters 10-13. When explaining why EUM appears so late in Portfolio Selection Markowitz writes, “The reason these fundamental assumptions appeared at the back of the book rather than at the front was that I feared that if I started with an axiomatic treatment of the theory of rational decision making under uncertainty, no one involved with managing money would read the book.” Valid point, Harry.
Renowned economist John Maynard Keynes outright rejected the notion that individuals seek to maximize utility. He wrote in his General Theory: "The classical theory assumes that the economic subject is always in a state of full and deliberate rationality and that his choices are always consistent and unchanging. The theory assumes that the subject is always in a position to maximize his satisfactions, so that his actions can be described in terms of a definite preference ordering." He argued that this abstraction was too broad and that theories built on this assumption were not valid in the real world. His solution was to take a much more nuanced view of how individuals make decisions and advocated using Descriptive methodologies instead of Normative.
As we have said many times, the mathematics of Modern Portfolio theory are correct. Too many critics focus on whether the MPT requires a normal distribution of returns and volatility, or if skewness (asymmetrical curve) and kurtosis (non-uniform shape) invalidate the results. This line of argument is irrelevant because it is the very foundation of the theory that should be examined. Our disagreement with MPT is as follows:
MPT is explicitly based on a Rational Decision Maker operating under a normative framework. This assumption is explicitly impractical. Human investors are subject to behavioral biases and use emotions to satisfice when decision making, especially while under duress. They sell when things are down and buy when things are up. They hold their losses forever and sell their winners to harvest gains. They make decisions based on limited data and allow the fear of missing out to cause them to exhibit herding behavior.
MPT assumes the market is efficient and that all information is immediately reflected in stock prices. If our fellow investors want to play poker against us without looking at their cards, I welcome them to the table. It reminds me of the two economists who were walking down the street and one of them sees a $20 bill. When one of them stopped to pick it up his companion stops him and scolds him that the bill cannot exist, because if it did someone would have picked it up already. They both moved on content in their vastly superior understanding of the world.
MPT assumes that infinite diversification is beneficial. Because MPT uses variance to calculate risk, upside volatility is punished just as severely as downside volatility. Markowitz mentioned that semi-variance may be a better measure, but his computer was not strong enough to do the math consistently in 1959. Here we are almost 65 years later with computers in our toasters more powerful than what sent a man to the moon, and we are still using variance. We believe that good decision making allows us to skew our volatility to the upside. Modern research calls this “active share”, and it has been shown to increase returns.
MPT assumes investors are homogenous. Markowitz explicitly states that Portfolio selection is intended for large, well-diversified institutional investors. Your average 70-year-old retiree does not have the same ability to weather financial storms as a large foundation or pension fund. They do not have equal timeframes or ability to raise funds if a down market wipes out 50% of their net worth. A foundation is run by allegedly educated businesspeople, and the retiree may have little math past basic algebra. MPT does not take individual circumstances into account.
MPT uses historical data to make estimates of the future. It relies on reason instead of judgement. In our experience, past results are misleadingly consistent until they are not. A large increase in security prices may cause them to be above fair value, which will normally mean revert and correct in price to a point significantly below fair value. These moves may take years or decades to materialize and can be detrimental to those who overly rely on trends.
Markowitz gives no advice on how to calculate the inputs, which are usually referred to as “Capital Market Expectations”. No two sets of CMEs are the same. If all the brain power in finance cannot figure inputs that are reasonably similar, what hope do we have that they are remotely correct?
Average annual returns are a terrible method of tracking your progress. There is nothing special about a trip around the sun that makes it advantageous to utilize as a yardstick for measuring success. Returns are not linear, and equity prices exhibit significant price fluctuations regardless of increasing value. It is much more instructive to use your continued ability to maintain your lifestyle as a hurdle for success. We use average annual returns in MPT in order to create an artificially discrete game, as opposed to a continuous game, which requires calculus.
At Basepoint, we mix experience with reason when determining your appropriate asset allocation. We evaluate your individual goals and constraints when determining how much risk to take with your money. A big part of this process is determining your liquidity needs and your ability to withstand fluctuations in your portfolio values. We attempt to avoid large drawdowns by being careful and knowing what we own. An advisor works with you directly to determine both your ability and your willingness to accept volatility. We then examine your time constraints, your tax constraints, your legal constraints, and other constraints that need to be taken into consideration. Once this process is complete, we build a portfolio by blending a model portfolio and your individual circumstances.
Our models are based on the assumption that an average investor would consider a reasonable amount of risk to be 60% risk assets and 40% fixed income assets. This is an experiential approach and is one methodology described in the CFA Institute guidebook, “Managing Investment Portfolios”. We then build our expectations about returns based on current circumstances. We utilize earnings yields and fair value to evaluate potential stock returns and we utilize interest rates and spreads to evaluate potential bond returns. We also evaluate alternative investments and investment strategies in periods of time where returns on both stocks and bonds appear to be unsatisfactory. Finally, we allocate portfolio cash to provide stability, liquidity, and potential funds for future purchases when market prices are too high.
Much has been written this year about the death of the 60/40 portfolio. This is true only if you combine this strategy with passive indexing, and if instead of using it as a starting point you use it as an inviolable rule. We use 4 major asset classes instead of 2. We allocate between equity, fixed income, cash, and alternatives. We use security selection as an important component of our investment allocation, and we do not consider all assets classes to be equal. Our performance last year in comparison to a typical 60/40 allocation made of passive index holdings illustrates this clearly. Our mean return outperformed a standard index portfolio by around 8%. We always attempt to eliminate the risk of ruin, even if it costs us a little return in the short-term.
Our methodology may seem inferior because it is not based on fancy mathematics, but as Keynes once said: “I’d rather be vaguely right than precisely wrong”. This process takes your individual circumstances into account, allocates capital based on current risks, not past risks, and protects you from catastrophic failure instead of utilizing a probabilistic function meant to measure an undefined esoteric concept like “utility”. You can’t eat utility and it won’t keep you warm on a cold night. Further, utility does not apply sufficient weight to catastrophic failure. How would you quantify the way you would feel if you had negative infinity utility? The pain of being cold and starving is not equally weighted against the pleasure of being warm and full.
It would not be hard for us to use conventional methodology. We understand it better than most, the software is cheap, and we could claim intellectual superiority to all who challenge us. The mathematics of MPT really are elegant, but as Albert Einstein said, “If you are out to describe the truth, leave elegance to the tailor”. The problem is that we truly do not believe that doing this would lead to better results, and it could possibly lead to worse results, like 2022. Career risk is one of the main reasons that the finance industry has adopted these concepts. Hopefully the day never comes when these faulty techniques are legally mandated.
The reason that these are important concepts to lay out is because most investment practitioners are utilizing these strategies without ever having read or understood Markowitz. They uncritically follow this mathematical charade without understanding its flaws. It is important to break these concepts down to show exactly why we have chosen a different path. If you fail conventionally people call you unlucky, but if you fail unconventionally people call you an idiot. It is important to document our decision-making process and explain why we feel like a more common-sense methodology is an improvement over mathematical precision based on faulty assumptions.
As for those two bold statements at the beginning of this letter: The sky is clear, but it appears blue from the ground due to the short waves of blue light being scattered more than the other colors in the visual spectrum. A picture from a satellite will show that you can see the ground clearly from above. And the Earth is not “round”, it is an oblate ellipsoid; it bulges at the equator. This is caused by centrifugal force created by Earth’s rotation. Every now and then we need to cast doubt on the things that we have long held to be certain.
Thank you again for trusting us to help you reach your goals. Our principles and process are based on what we believe to be the most precise and accurate methods available to lead you to financial success. We examine form as well as function and we try to make sure that everything that we do is logically consistent. We will not substitute fancy mathematics for common sense. We will define financial success as making your assets last as long as you need them to, and then longer. If you have any questions about the way we do things, please do not hesitate to contact your advisor, or me directly.
Warm Regards,
Allen
*An options contract in which one sells the opportunity to be forced to deliver a security at a certain price in the future. In a “naked call option” the seller does not own the underlying shares to deliver, and if demanded they would need to purchase the securities in the open market. This contractual arrangement is one of the few instances in finance that contain unlimited loss potential.
Basepoint Wealth, LLC does not guarantee results. Past performance is not indicative of future results. All investments carry risk, and no investment strategy can guarantee a profit or protect from loss of capital.