Vice President Kamala Harris’s chance of winning the U.S. presidential election is lower than it was two weeks ago, according to a model that uses the stock market’s year-to-date performance to predict the incumbent political party’s likelihood of victory.
Nevertheless, that model still predicts that Harris, the Democratic presidential candidate, is likely to win the presidency on Tuesday — giving her a 70% probability of victory. The reason Harris’s likelihood of winning was lower on Nov. 1 than the 72% where it stood on Oct. 17, when I last wrote about this model, is that the Dow Jones Industrial Average has declined in the interim.
This stock-market prediction model is not complicated. It exploits the historical tendency for the incumbent political party’s chance of electoral victory to reflect the Dow’s year-to-date performance. The model’s track record is statistically highly significant — at the 99% level.
Take a look at the chart above. It plots the trendline that best fits the historical data back to 1900. Is the model foolproof? Of course not. And bear in mind that a 70% probability is not 100%. Furthermore, even if the model had a perfect track record, there’s no guarantee that the future will be like the past.
People tend to vote their pocketbooks.
That said, my simple model does have a better track record than the majority of models Wall Street uses, many if not most of which have no statistical validity. The model makes theoretical sense: The stock market is forward-looking, so a rising market means that most investors are upbeat about the economy’s prospects in coming months. Numerous studies have found that people tend to vote their pocketbooks...
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