NYU economist (and 2003 Nobelist) Rob Engle has a piece in today’s FT about the area of his expertise, volatility:
An understanding that the fundamental cause of volatility is new information will help assess when it might return to normal. Basically, asset prices change when there is new information, used by analysts and investors, to forecast future values and risks. Some of this information is the standard economic data used by traditional analysts; some may be measures of risk tolerance or other market indicators; and some could be false information. Some information comes from official sources and some comes from the observation of trade flows that can reveal private information. New information comes in clusters leading to the well-known observation of volatility clustering in financial markets. So a way to understand volatility is to ask: when is there likely to be lots of new information?
Engle then refers to some research he’s done recently to determine the “five macroeconomic features associated with high volatility.” They are (1) high inflation, (2) low GDP growth, and high volatility of (3) inflation, (4) GDP growth, and (5) interest rates. I don’t know about you, but to me this is spectacularly unhelpful. When the economy is struggling and economic variables are volatile, market prices are volatile. We knew that, professor. But could Engle have used this information to predict in early 2007 that market volatility was about to switch from normal to abnormal? No. Not at all.