“The short-term volatility of price will be greater than the short-term volatility of value.” –Fisher Black
In 1986, Fisher Black attempted to explain the concept of “noise” in financial markets. He said that “noise is what makes our observations imperfect. […] It is information that hasn’t yet arrived.” He claimed that if noise trading didn’t exist, there would be very little trading in individual assets. Put another way, noise trading results in liquidity.
Twenty years later, in a piece in The Wall Street Journal, Jeremy Siegel contrasted the “noisy market hypothesis” with the idea of market efficiency. He stated that stock prices are not always the best estimate of value because “prices can be influenced by speculators and momentum traders.”
While noise in prices has been cited in numerous academic articles examining value and size premiums, it’s not a term with a singular definition in finance, nor is it well understood. Noise and volatility are often mistaken for one another. As counter-trend traders, we attempt to take advantage of noise in financial markets. To do so successfully, we must have a precise understanding of the differences between noise and volatility, and the ability to measure those distinct phenomena.
We believe that “noise” measures the choppiness of the market’s price path, while “volatility” measures the magnitude of the market’s price changes. One way to quantify noise is by measuring the smoothness of a price series’ path; this is done by examining the ratio of the net price movement over a time period relative to the total up and down movement. This ratio quantifies the percentage of an asset’s movements that were congruent with its underlying trend, or the percentage of net directional movement.