November 8, 2016


Why Bettors Take a Flier on Trump (Leonid Bershidsky, 10/31/16, )

[H]ere are some serious and whimsical indicators to give Trump bettors hope.

Social network engagement and Google searches. "Big data" analysis is an increasingly popular crutch for investors and analysts who don't fully trust polls. More people are searching for Trump on Google, and "vote Trump" is a far more popular search request than "vote Clinton." On the USA Today/Facebook candidate barometer, Trump demonstrates much better Facebook engagement, seen as the combined number of likes, comments, shares and posts. Most of those who "like" and share posts mentioning Trump could be haters, not backers. Yet a study of Twitter activity, which uses content analysis, shows that Trump has a consistently better ratio of positive to negative tweets than Clinton. That's a warning to Clintonites: Brexit supporters dominated the social networks before the U.K. voted to leave the EU in June. An artificial-intelligence system that analyzes social network data, built by Shajiv Rai, founder of the Indian startup, in 2004, predicts a victory for Trump. It accurately called the last three U.S. presidential elections.

Economic indicators. Several econometric models that predict electoral outcomes based on the incumbent party's economic performance forecast a change of ruling party this year. Alan Abramovitz of the University of Virginia, whose model has accurately called the popular-vote winners since 1988, gives Clinton 48.6 percent of the two-party vote (with the caveat that Trump's personality may well move the needle in the Democrat's favor). A 2009 model by Yale's Ray Fair reflects the relationship between economic indicators (output growth and inflation) and votes cast for the incumbent party's candidate. This model has consistently predicted a loss for the Democrats this year. As of Oct. 28, Fair's model gives Clinton 44 percent of the vote in a two-way race. In 2012, Fair's equation gave Obama 49 percent; he ended up with 51 percent, within the model's 2.5 percentage-point margin of error. If Clinton wins, it will be the first time the model will prove inaccurate. Unemployment dynamics and the ISM Manufacturing index, which have been good predictors of election outcomes, also give an advantage to Trump as the change candidate.

Consumer confidence. The measure for October of the presidential election year has long been highly predictive of the outcome of the race, as Mitsubishi Bank vice president Michael Nemira argued in a 1992 paper. Nemira used a simple formula involving the University of Michigan's Index of Consumer Sentiment that has only failed in 2000 (when the incumbent party's candidate did win the popular vote but still lost the election) and in 2012 (when one could argue that consumer confidence hadn't recovered after the 2008 financial crisis). This year, the formula predicts a loss for Democrats. There's another, even simpler way to use consumer confidence to predict presidential race outcomes. Since 1968, the incumbent party has won nine of the 12 elections when the Consumer Confidence Index was above 100. The exceptions were 2012, 2000 and 1968, when President Lyndon Johnson decided to forego a re-election bid amid turmoil over the Vietnam War. It stands at 98.6 now, predicting a victory for the Republican nominee.

The fiscal model. Based on the observation that growing federal spending relative to the gross domestic product reduces the incumbent party's chances of winning, it failed to predict Barack Obama's re-election in 2012. Its author, Alfred Cuzan of the University of West Florida, has since adjusted it. The model predicts a loss for the Democrats, with 48.2 percent of the two-party vote.

Helmut Norpoth's models. The SUNY at Stony Brook professor has two. One is based on the candidates' primary performance: The one who does better in his party's early primaries wins the election. This has been true in every election since 1912 except the 1960 one. The model predicts a strong likelihood of a Trump win. The other one, based on the view that "like sunspots, elections run in cycles" -- an approach to politics reminiscent of the technical analysis traders use -- projects a victory for Trump with 51.4 percent of the popular vote. Norpoth is on record as saying that polls are "bunk" because they are about opinions, not actions. He is convinced Trump is headed for victory and has bet on him on the Iowa prediction markets.

Allan Lichtman's "13 Keys to the White House." The American University professor's previously accurate approach is also largely based on the outgoing administration's performance. Of the 13 indicators, including the state of the national economy, social unrest, scandals, the incumbent's foreign policy success and both top candidates' charisma, five should point in the challenger's favor for him to win. Lichtman predicts a Trump victory. that it was essentially unloseable for the GOP.

Posted by at November 8, 2016 8:45 PM