“True wisdom comes to each of us when we realize how little we understand about life, ourselves, and the world around us.” Socrates
When I read the Socrates quote above I can’t imagine what he would have said about today’s world. We live in a highly complex non-linear world with access to way more information than even massive computers can process. And yet we try and get by with our relatively poor information processing brains that simply cant deal with the onslaught of data and are subject to slews of behavioral biases which affect our decision making. No where is this more true than investing where there is the added complexity of trying to predict the future under in such an environment. I was reminded of this recently by a white paper from one of my favorite quantitative investment researchers Wes Gray titled Are you trying too hard? In the paper he makes the case for systematic decision making, i.e. quant investing. It’s a compelling case that all investors should consider. I’ll highlight some of the gems in the paper but by all means read it all and try a take a few minutes from the information hose to digest what it could mean for you.
First, lets start with the basic summary of the white paper;
Because we recognize our frequent irrational urges, we often seek the judgment of experts, to avoid becoming our own worst enemy. We assume that experts, with years of experience in their particular fields, are better equipped and incentivized to make unbiased decisions. But is this assumption valid? A surprisingly robust, but neglected branch of academic literature, has studied the assumption that experts make unbiased decisions for over 60 years. The evidence tells a decidedly one-sided story: systematic decision-making, through the use of simple quantitative models with limited inputs, outperforms discretionary decisions made by experts.
The evidence is overwhelming. He understates his case. And its even worse than he makes out as investors even underperform the experts they are paying to underperform the market by chasing returns. The solution lies in relying on models and focusing our precious limited bandwidth on choosing said models and evaluating their performance.
Students of decision-making break the decision-making process into three components (see Figure 3):
- Research and development
I would argue that human experts are required for the first and third phases of a decision-making process, which are the research and development phase and the assessment phase, respectively. The crux of my argument is that human experts should not be involved in the second phase of decision-making, or the implementation phase.
Exactly. Focus on the model and how it performs. This need not be a complex quant model. Standard allocation and Buy and hold indexing is a model. A model that can work quite well for most investors over the long term. The IVY portfolios whether buy and hold or the trend following ones are models. So are all the quant portfolios I’ve discussed on the blog. Once you decide to go on a path to more systematic decision making, the question becomes which one is right for you. Buy and hold is just fine if you can handle the drawdowns in bad years. Many can’t. Then what? Choose a different model.
What’s even more enlightening is that even experts armed with proven models under perform the model. How’s that for human fallibility. Turns out the models represent a ceiling on performance.
In follow-on tests, the researchers gave the experts the output of the model and disclosed that the model has “previously demonstrated high predictive validity in identifying the presence or absence of intellectual deterioration associated with brain damage.” Using the model, experienced clinicians significantly improved their accuracy ratio from 58.3% to 75% and the inexperienced clinicians moved from 62.5% to 66.5%. Nonetheless, the experts were still unable to outperform the stand-alone model, which had already established the gold standard 83.3% success rate. This study suggests that models don’t represent a floor on performance; rather, models reflect a ceiling on performance, from which the experts detract. The “secret sauce” of human judgment ruins the beautiful simplicity of a calculation
What this tells me is that I need to accept that even after I make the conscious decision to use models I shouldn’t expect my performance to equal the model. Inevitably I will get in the way of the model and mess things up. That’s OK. We are not robots nor can we expect to become one but we should strive to adhere to the models and/or find ones that better fit our individual behavioral biases. This is not an easy switch to make.
Relegating your decision-making processes to systems requires a massive dose of humble pie.
Most—if not all—are unable to consume this dish. But to be a better decision maker we must eat our humble pie. As I have shown in this essay, in order for decision making to be effective, it must be systematic. And the only systematic thing about humans is our flaws. Therefore, it is best to leave the stock picking to Warren Buffett, and for the rest of us, who suffer from behavioral biases, which result in flawed decision making, we should stare into the mirror, and ask ourselves: Are You Trying Too Hard?
Yes, I was. And probably still am. My personal journey to quant investing started in 2005 when I bought two books that began a fundamental shift in investment thinking. The first book was Joel Greenblatt’s The Little Book That Beats the Market and the second was O’Shaughnessy’s What Works on Wall Street (links are to newer editions of the books). Then in 2009 it was The IVY Portfolio by Meb Faber which introduced me to ETF systems and risk reduction with trend following. That began a slow transition to quant investing and benchmarking myself against models. I’m now down to one individual discretionary stock holding and still a bit too discretionary for my bond holdings but I’m almost to where I want to be. My conclusion after all of this; even if I assume I can beat the models, which btw can beat the market, with above-average stock picking ability or market timing it’s not worth the time, work, or anxiety. I have better things I can do with my time and energy. You have probably been trying too hard too.