After the post on Fama’s rebuttal of Moving Averages (and a few strong reactions to it), it might be worth taking a more balanced look at the argument. Andrew Lo introduced the Adaptive Market hypothesis (AMH) in a 2004/2005 paper (download here).
With the AMH, Lo attempts to reconcile the Efficient Markets Hypothesis with behavioral models, which often seem to contradict each other. The AMH is based on “Darwinian” evolutionary principles:
Based on evolutionary principles, the Adaptive Markets Hypothesis implies that the degree of market efficiency is related to environmental factors characterizing market ecology such as the number of competitors in the market, the magnitude of profit opportunities available, and the adaptability of the market participants.
Behavioral biases are, in fact, consistent with an evolutionary model of individuals adapting to a changing environment via simple heuristics.
The EMH model can be seen as the equilibrium state in a perfect/ideal world where market efficiency runs at 100%. However, reality is often more complex than a simple theoretical model. Because of ever-changing factors, real market efficiency oscillates towards and away from the “perfect” EMH model, without necessarily converging towards it.
The framework that Lo describes is mostly qualitative and as such its applications might not be immediate.
The Behavioral Side
Lo covers some well-known behavioral biases to illustrate how “investor idiosyncrasies” contradict the EMH assumption: investors are not always rational.
Examples of behavioral biases used for illustration are:
- Probability assessment
- Risk aversion
These behavioral biases are presented as being investor heuristics:
Within this paradigm, behavioral biases are simply heuristics that have been taken out of context.
Given enough time and enough competitive forces, any counterproductive heuristic will be reshaped to better fit the current environment. The dynamics of natural selection and evolution yield a unifying set of principles from which all behavioral biases may be derived.
The EMH Response
The way EMH proponents address these questions raised by behavioralists is by affirming that markets as a whole gravitate towards efficiency. All “small” inefficiencies are arbitraged away and their effect counteract each other. The argument is that behavioral biases are negligible and irrelevant.
But this last conclusion relies on the assumption that market forces are sufficiently powerful to overcome any type of behavioral bias, or equivalently, that irrational beliefs are not so pervasive as to overwhelm the capacity of arbitrage capital dedicated to taking advantage of such irrationalities.
Lo then uses anecdotal evidence in the form of various classic financial manias and panics (tulip mania, South Sea Bubble, Dot-Com Crash, etc.) as examples that sometimes, forces of irrationality can dominate the forces of rationality.
A Look from the Neuroscience Angle
Behavioral finance falls into the field of psychology rather than economy and Lo takes a look at neuroscience to get a better understanding of behavioral biases.
EMH proponents sometimes criticize the behavioral literature as primarily observational, an intriguing collection of counterexamples without any unifying principles to explain their origins. To a large extent, this criticism is a reflection of the differences between economics and psychology.
The field of psychology has its roots in empirical observation, controlled experimentation, and clinical applications. From the psychological perspective, behavior is often the main object of study, and only after carefully controlled experimental measurements do psychologists attempt to make inferences about the origins of such behavior.
In contrast, economists typically derive behavior axiomatically from simple principles such as expected utility maximization, resulting in sharp predictions of economic behavior that are routinely refuted empirically.
In this section, Lo gives us (succinct) explanation of how the brain works and how it can be split in three parts: reptilian, mammalian and hominid brains, all traces of our evolutionary past. These “three” brains react to and manage situations differently. The way they interact when presented with “emotional distress” (fear and greed for example) is likely the root of behavioral biases: Emotion is at the heart of irrational decision.
The Hypothesis and its Implications
Lo’s theory falls in the “Darwinian alternatives to the EMH”, arguing that individual investors develop heuristics to solve various economic challenges, based on their experience. They learn by receiving positive or negative reinforcement from the outcomes. If the environment remains stable, heuristics will tend towards optimal solutions. However, with changing market environments, heuristics become unsuited and need to adapt: this is when behaviors can appear irrational.
- Individuals act in their own self-interest.
- Individuals make mistakes.
- Individuals learn and adapt.
- Competition drives adaptation and innovation.
- Natural selection shapes market ecology.
- Evolution determines market dynamics.
Any market will be more or less efficient depending on its ecology (ie number and variety of market participants, availability of profit opportunities). However, convergence to equilibrium is neither guaranteed nor likely to occur at any point in time (as per concepts of evolutionary biology).
Lo concludes with applications of the AMH, to try and render his model more practical.
- Investor’s preferences matter and need to be managed to meet their objectives.
- Risk/Reward relations are likely to evolve over time.
- Arbitrage opportunities do exist from time to time. The market does not necessarily tend to higher efficiency but is subject to more complex market dynamics with cycles and market trends.
- Specific investment strategies’ profitability evolves over time
- A better way to achieve a consistent level of expected returns is to adapt to changing market conditions
As Lo warned us in the introduction, this work is still at a level of qualitative framework of thoughts, and as such still needs to be developed if it wants to compete with the EMH theory – which, despite being flawed, provides more practical applications for an investor.
The main practical application from the above points hints at the idea of using regime switching to adapt a trading strategy to the changing market environment.