An Overview of Our Investment Philosophy
Our research is based on the application of complex adaptive systems theory to investing (also known as the adaptive markets approach; for example, see Professor Andrew Lo's excellent work).
All complex adaptive systems share some common characteristics. They are filled with adaptive agents (e.g., human or algorithmic investors) who are constantly updating their strategies (e.g., value, momentum, sentiment-driven, passive, etc.) at varying rates of speed in light of the results they are producing relative to the goals they seek to achieve (e.g., outperform an index, meet a minimum-multiyear compound annual real return target, etc.)
These agents must make decisions with imperfect information (about both individual assets and the operation of the overall system) and limited information processing capacity (both cognitive and computer based), under the influence of time pressure and individual emotions.
Individual agents are also enmeshed a dense network of relationships, so that their actions result from a combination of their own assessment of available information, as well as the social influence of other agents to whom they are directly or indirectly connected.
This mix of factors and interacting feedback loops frequently causes the aggregate behavior of complex adaptive systems (e.g., asset values and returns) to be characterized by time delays and non-linearity. They also cause the behavior of such systems to be extremely difficult to accurately predict. Moreover, this challenge becomes exponentially more difficult as the forecast time horizon lengthens.
As is the case with other complex adaptive systems, while financial markets are attracted to equilibrium, they never reach it, and can be driven far away from it, which produces substantial asset and asset class over and undervaluations.
In complex adaptive markets, we believe that the following seven step approach maximizes the probability that an investor will achieve their long-term investment goals.
First, develop a clear understanding of how your current and expected future savings, years to retirement, desired post-retirement investment income, and target bequest interact to determine the minimum compound annual real rate of return you need to earn on your portfolio. In our view, investing is not about annual returns relative to an index; it is about achieving your long-term goals.
Second, recognize that because investment returns vary and interact, your target portfolio rate of return will usually have to be higher than the minimum rate of return you need to earn to reach your goals.
Third, regularly update these calculations as your goals and circumstances change over time. We are not among those who believe that you should start with long-term goals and a quiz to determine your "risk appetite" and with that as an unchanging anchor, derive all the other elements of an investment strategy (e.g., savings rate, asset allocation). In our experience, risk appetite varies both with circumstances and the passage of time.
A simple case in point: People normally don't run into burning buildings (firefighters and police excepted). But if your child was inside, you wouldn't hesitate. For us, the key point is that investors should make (and revisit over time) conscious tradeoffs between their goals, savings rate, degree of risk, asset allocation, and choice of an active or passive approach to implementing it.
Fourth, appreciate both the importance of asset allocation to the returns your portfolio will earn and methodological challenges and uncertainties it entails. Seek robust asset allocation solutions that will, given what you know today, maximize the probability of achieving your target portfolio return (subject to a maximum shortfall constraint) under a wide range of future scenarios.
Fifth, remember that as your minimum target rate of return evolves with your changing goals and circumstances, your asset allocation will probably also need to change.
Sixth, recognize that avoiding big losses has a greater mathematical and emotional impact on achieving your long-term financial goals than stretching for big gains, and that substantial overvaluations are usually much easier to identify than substantial undervaluations.
This means you need to be disciplined about rebalancing your asset class allocations, vigilant about extreme overvaluations, and willing reduce your exposure to them when they occur, even at the (social) risk of “getting out too early” (i.e., missing out on that last bit of upside return before prices crash).
Seventh, think carefully about the mix of active and passive investments you will use in your portfolio to implement your asset allocation strategy. While actively managed investment products have a legitimate role to play in many portfolios (e.g., uncorrelated pure alpha products), successful active investment is expensive, and doesn't just depend on having some forecasting skill.
Rather, it requires that your forecasting skill be consistently superior to the average skill level possessed by the other active managers against whom you are competing. This is a far higher bar than most people like to admit, and one that has grown much more challenging as algorithmic trading has come to dominate many financial markets.
Learn more about our approach to asset allocation.
Learn more about our approach to active versus passive investing.