The Fallibility of Investment Models
Investors who place too much faith in the investment models could be lulled into complacency which could leave them vulnerable to unexpected events.
With the advent of computers in the 1980s, investment advisors have turned to investment models to provide investors with guidance on how to create the best portfolio for their specific objectives. Many of these models, grounded in academic theories such as Modern Portfolio Theory or Asset Allocation based on risk calculations that imply knowledge of future uncertainties, which really can’t be done. While lab-generated portfolio models have shown to be useful for analyzing historical returns, an overreliance on them for making future-facing investment decisions can prove detrimental if real world events aren’t factored into the projections. Investors who place too much faith in the models could be lulled into complacency which could leave them vulnerable to unexpected events.
Investment advisors use portfolio model forecasting to help guide investors in their selection of investments based on their stated tolerance for risk, investment preferences and clearly defined objectives. After incorporating all of these factors into a computer program, the software spits out hundreds, sometimes thousands of hypothetical projections and then narrows them down using probability algorithms. When the highest probability quotient is achieved, that becomes the model portfolio that guides the investor’s or advisor’s decisions.
Investment Model Flaws
There are, essentially two fairly significant problems when using portfolio modeling. The first is that none of these various model theories have ever proven their validity. They have always worked well on the chalk board, but nothing has ever been presented that demonstrates their accuracy in actual investment planning. Nobel Prizes have been awarded to theorists who have yet to prove that their theories can work in the real world. In fact, there is ample evidence to show that adherence to these models by investors has led to consistent underperformance.
The second, perhaps even larger problem is that these models don’t account for major calamitous events - major terrorist strikes, massive tsunamis, nuclear meltdowns, financial meltdowns, geo-political upheavals - which can change the course of economies and markets in an instant. These events, often referred to as “Black Swans” because they appear so rarely among the more normal white swans, have never been factored into models or theories because they are highly “improbable”. While they have historically been less probable, their impact on the markets has usually been substantial.
Models that exclude the possibility of such events can never be reliable in their projections. And the fact that we seem to be experiencing Black Swans more frequently than at any other time, the models are more likely to underestimate the risks and reality investors face leaving them extremely vulnerable. The markets today are much more volatile than they were back when these theories and models were developed. Model theorists may never have imagined a stock market that could fall 10% in a single day, or 40% in a matter of months. But, millions of investors have lived it in recent years.
Portfolio models assume that, collectively, investors will act rationally. But the steep stock market declines and wild gyrations of recent years clearly demonstrate otherwise. When you toss in a Black Swan or two, people just become crazy.
This is not to suggest that portfolio modeling doesn’t have its place. Investors should use all of the tools at their disposal to formulate sound long-term plans and make informative decisions. But, investors shouldn’t rely exclusively on mathematical formulas or hypothetical projections. While you shouldn’t totally ignore the “experts, it’s important to incorporate your own thoughts and base decisions on the certainty of your long term goals rather than uncertainty of future market performance.