IGOR!!! … My portfolio needs a boost. Fetch me some high-risk stocks,” declared Frankenstein. You see, the Doc was in a pickle. Castle costs were way up and heating the drafty halls was just the beginning. His once friendly contractors had rebelled and started to demand danger pay to fix the lightning machines. To make matters worse, the price of brains was getting, well, ridiculous. But his financial adviser had a solution. The Doctor could fund his exciting experiments by dialling up the risk level on his portfolio and thereby restoring his treasury.

While you probably don’t have a moat to tend, you’re likely familiar with the link between risk and returns. In fact, to many it is the most basic rule in investing: The more risk you take on, the higher your potential returns. But what if it isn’t true? What if, in fact, after a certain point, taking on more risk actually lowers your potential returns? It’s a controversial argument that seems to directly contradict the teachings of investing 101—but after spending many years carefully considering empirical studies on the matter, it’s an argument that I believe to be true. And just to be clear: I’m not saying that you should avoid risk because you could lose your money. That’s practically the definition of risk. What I’m saying is that historical evidence shows that above a certain point, the more risk you take on, the lower your potential returns.

The trouble with measuring risk
Before I defend my position, let’s back up a bit and look at how risk is commonly defined. After all, risk is a malleable term that can cover a wide variety of circumstances and meanings. The word “risk” is very often misused—and even more often misunderstood.

To most investors, risk is related to the chance of losing money and to the size of potential losses. But even here risk is already a complicated multi-factor beast. Worse, it’s easy to dream up all sorts of potential dangers from the fanciful to the everyday. For instance, you’re not going to worry much about the possibility that your company’s factory will be destroyed by a giant block of falling cheese. On the other hand, smaller frequent losses like those due to shoplifting are an important concern for retailers.

What we need is a way to sum up all the risks that might cause a stock’s price to fall. And indeed some academics gave producing such a measure the old college try. Most famous is the late 20th century’s classic definition of risk which is encapsulated in a strange concept called “beta”. Beta is a risk measure that puts a number on the tendency of stocks to move in sync with the markets. It is related to a combination of how volatile a stock is (or how much its returns vary) and how closely it moves (or is correlated) with the market as a whole. Both factors are important.

Roughly speaking, stocks with a beta of 1 tend to move in sync with the market. Those with a beta of 0 tend to move independently of the market, while stocks with negative betas tend to zig when the market zags. (By definition the overall market has a beta of 1.) Thus, a stock that jumps around a lot (highly volatile) and moves in tandem with the market will have a high positive beta and is considered risky. While a placid stock that doesn’t move much and doesn’t seem to be impacted much by the market will have a small beta and is considered to be less risky. But keep in mind, beta is based on stock returns (think percentage moves) and not prices. As a result, stocks with very similar betas may have wildly different price patterns because a small return mismatch can grow significantly over time.

But even if beta is a good measure of risk, we still have not answered a much more important question: Where did that original misguided idea that you get higher returns by taking on more risk come from?