Some interesting recent research has shown that people generally make decisions intuitively before using their conscious thought processes to justify them. No one is rational, at least to the degree that they think they are. This idea also means that the line between thoughts and emotions is rather porous. Decisions are going to be influenced by moods, just as they are by more coherent thoughts. So perhaps it should be no surprise that weather influences traders, and hence the markets. People tend to be in better moods when the weather is pleasant.
(And of course, weather events have very clear effects on certain industries and sectors such as energy and tourism. But these drivers are catastrophic events like hurricanes, not the difference between a 75-degree day in March and a week of rain in June.)
In their paper, “Do Weather-Induced Moods Affect the Processing of Earnings News?“, Ed deHaan, Joshua Madsen, and Joseph Piotroski show that unpleasant weather negatively affects market participants moods and causes a more muted reaction to news. In particular, analysts experiencing bad weather are less likely to update their forecasts in response to earnings than those working during periods of nice weather. And at the aggregate market level, this leads to a smaller initial reaction to the earnings announcement and a greater subsequent price drift as the market slowly adjusts.
Specifically, a one standard deviation in their “unpleasant weather” measurement translates into a 5% decrease in the chance of an analyst issuing a forecast change. This change also leads to a 6.5% decrease in the chance of a recommendation (buy/sell/hold) change. These returns don’t seem enormous, but they might still be economically significant (again, refer to our post “Small Edges Add Up“). Keeping track of the New York weather seems like a plausible “micro-alpha” to add to a portfolio of edges.
There have been other papers studying the effect of weather on the equity markets. For example:
The possible effect of the weather is not currently in our models. But it is an example of something we will test. In investing research, as in love, you need to kiss a lot of frogs.
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