How can we tell the signal from the noise?

Photo: Doug Tengdin. Source: Wikipedia. Readings from a device with poor signal isolation. The middle of the plot shows lower noise levels

A signal-to-noise ratio is a good way to think about markets. Every day, the media pushes out TONS of information about the economy, interest rates, markets, companies, politics, and on and on. That’s their business: generating clicks, likes, retweets, and attention. But a year or more from now, most of those headlines have been lost in the background buzz of market-related news coverage. Remember Covid’s Delta variant? News of how several athletes caught the Delta variant at the Olympic village had many people worried. But now most of us barely remember that the Olympics were last year, much less that Delta almost derailed them.

The vast bulk of daily market information fits the classic definition of noise: meaningless or unwanted disturbance. It interferes with radio signals, measurements, weather instruments, and anything else we want to monitor. If you and a friend are trying to speak while driving a convertible with the top down down the interstate or in bumper-to-bumper traffic when everyone is honking, you know exactly what noise does. It makes it a lot harder to hear what’s really going on.

The key to handling noise is to have a proper filter – something that strips away the extraneous information and leaves you with what’s important. Radio engineers use “gaussian filters” to reduce the static generated by their broadcasts. The filter would be customized to their intended use. Modern algorithmic trading systems use similar gaussian techniques with market data to try to find profitable short-term signals. These algorithms sometimes create dozens of positions and close them out within the same second, so their filters have to be very specialized.

Early radio noise filter patent application. Source: Free Patents Online.

Just as radio signal filters depended on the purpose of the transmission, a lot of what goes into our filter depends on our goals. The most important signals aren’t about economics or interest rates or even corporate earnings (my favorite data), they’re about ourselves: our health, our employment, our family finances. Next is our ability to deal with the uncertainties associated with investing: our ability to to take on risk, our attitudes about risk, and how we might respond to a loss. A lot of people find that their attitudes about risk change when the market falls.

Next comes what reasonable expectations we may have of the market in general, including the effect inflation may have. If we’re investing to create a retirement nest-egg, we’ll need different inputs than if we’re saving for a down payment on a mortgage. Most people have several goals; it’s helpful to put those together in a comprehensive plan.

You might notice I didn’t include market chit-chat as an inputs. That’s because it’s usually not relevant until the last stage, putting a portfolio together. Portfolio construction has to do with how we invest – active vs. passive, stocks vs. bonds, global vs. domestic. There’s an optimal mix for every investor, based on their unique objectives, constraints, personality, and financial circumstances. Every investor is unique, and needs a customized solution tailored to meet their specific needs.

Growth of a dollar since 1925 invested in various asset classes. Source: Ibbotson, CFA Institute.

There are some strong signals amid the noise of the financial world. The most important signals are the ones we should be transmitting to ourselves. Be sure THOSE aren’t filtered out!