Originally published in the Brandywine Asset Management Monthly Report.
Over the past few decades Brandywine has built a reputation as being an innovator. While this has served us well from a performance-standpoint, it has often led to confusion when investors attempted to fit us into the investment manager categories they had created. For example, being systematic, as we are, often leads people to believe we must be a trend follower, which we are not. Or it leads to the assumption that we do not use fundamental information, which we do. Over the years we have accumulated our answers to some of the most common questions and compiled these into a rather extensive Q&A document. We thought we’d post some of those related to our trading and risk management philosophy in this month’s report:
Please provide your insight into the behavior of markets. What market inefficiencies do you attempt to capture and why are these inefficiencies exploitable?
Brandywine does not attempt to exploit any single market inefficiency. Each trading strategy is developed by Brandywine with the intent of capturing returns from a specific Return Driver. There are numerous biases in people’s behavior related to trading/investing/gambling, and Brandywine seeks to exploit those biases. (This philosophy led to Mr. Dever writing his book Exploiting the Myths: Profiting from Wall Street’s misguided beliefs (which became a best-seller under the popular title Jackass Investing).
These biases include the desire to “trade with the crowd,” anchoring biases, risk aversion, and numerous other behaviors and emotional responses that create inefficiencies that lead to the development of profitable trading strategies. These strategies provide excellent potential returns and diversification value in a ‘rationally-structured’ portfolio such as Brandywine’s. For example, in Myth #3 of Mr. Dever’s book, titled “You Can’t Time the Market,” Mr. Dever shows that precisely because the majority of people buy and sell U.S. equities at the wrong time, if you can measure this activity you can fade it for profit. In the Action Section for the book, he presents a specific trading strategy that does exactly this by measuring the money flows into and out of U.S. equity ETFs. Other trading strategies gain their edge by the fact that they are ‘hard’ to trade. For example, they may be subject to high volatility of returns. Many traders prefer strategies with low volatility and therefore ignore exploiting sound return drivers that result in positive and predictable returns over time if those returns are too volatile. These strategies provide excellent positive returns and diversification value in a portfolio such as Brandywine’s.
Are there any counterintuitive implications to risk management that you derived from your model?
Certainly, the determination in the late 1980s that mean-variance optimization of a portfolio was fatally flawed was the first major counter-intuitive outcome of our research, as that was the most highly-regarded and accepted portfolio allocation model of the time (and to a large extent remains so today).
Second, many potential investors we talked with at that time were convinced that each individual trading strategy within our model was required to be able to “stand on its own” with regards to its risk-adjusted returns. Brandywine determined that the only relevant question at the individual strategy level was if the strategy was based on a sound logical return driver likely to provide it with a positive return over time. This led us to develop and implement many trading strategies that were, and continue to be, unique to Brandywine.
Please elaborate on your risk management plan. Do you have specific limits on exposure to markets/sectors or is it possible that several different portfolio strategies may signal positions in the same market/sector?
Brandywine’s portfolio allocation model is designed to provide balance across each strategy and market traded in the portfolio. This is intended to ensure that, over time, each market makes an equal contribution to the portfolio’s risk.
Brandywine takes a very “top-down” approach to risk management and portfolio allocation. Our belief is that if a portfolio allocation model results in a significant overweight of a market or related (correlated) group of markets, that is a symptom of a flaw in that model. Mike Dever covered this topic specifically in his well-received presentation titled “The Fatal Flaw in Mean-Variance Optimization” at the QuantInvest conference in NYC in 2012. Many managers address the flaw in their portfolio allocation models by imposing market or sector constraints, essentially putting a band-aid on the wound created by an incorrect (damaging) portfolio allocation model. Brandywine’s goal when Mike Dever developed our portfolio allocation model in the late 1980s – early 1990s was to create a model that – first and foremost – produced future results that matched, as closely as possible, past results. As logical as that sounds, it was novel then and continues to remain novel today. Most managers base the success of their portfolio allocation / risk management models on how well they “optimize” returns on past data, not on how well future returns are likely to match those past returns. They start their research by asking the wrong question – (“How can I get the best results?”, rather than “How can I get the most predictable results?”). Many (most) managers make that initial critical mistake of optimization vs. predictability. We discussed our “Predictive Diversification” portfolio allocation model in our November 2013 monthly report.
In response to the specific question:
YES – several of the underlying trading strategies can pick the same contract or market, but
NO, by design the portfolio allocation model will not significantly overweight any market. However, because multiple trading strategies agree on a specific trade/position, there is a higher probability that will be a successful trade. Our portfolio allocation model then naturally allocates more to higher probability opportunities but within the construct that future performance will continue to match past performance. So in summary, we WANT to have heavier allocations to positions when multiple trading strategies are in agreement.