Tag Archives: prediction

Nate Silver Breaks Down March Madness

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Your office may face a hit to productivity this week as staffers scramble to fill out March Madness brackets. Not here of course; we at the Chamber remain dutifully focused. For example, I'm writing this important blog … about college basketball.

Analyst/number cruncher Nate Silver gained a great deal of acclaim during the 2012 election by accurately predicting President Obama's return to the White House (although he also has a reputation for fantasy baseball prognosticating). So now he takes a crack at the 2013 NCAA tournament. Here's an excerpt, but read the entire piece for A LOT more detail:

Even before the N.C.A.A. men’s basketball tournament bracket was announced on Sunday, there was plenty of discussion about how much parity there was in this year’s field. The chatter only increased after Louisville, the No. 1 overall seed, was placed in a brutally tough Midwest region that also includes Duke and Michigan State.

This condition is nothing new, however. Parity has been the rule for some time in the N.C.A.A. tournament.

Louisville is in fact the nominal favorite to win the tournament despite its tough draw, according to the FiveThirtyEight forecast. Still, Louisville has only a 23 percent chance of doing so, just ahead of Indiana at 20 percent.

In 2012, the FiveThirtyEight formula listed Kentucky as the tournament favorite. That call looks prescient since the Wildcats went on to win. Still, the result involved as much luck as skill, since the forecast gave Kentucky just a 27 percent chance of winning, only modestly better than Louisville and Indiana this year.

Strange Criteria for Picking a Super Bowl Winner

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This week, there’s a lot of talk about the passing prowess of Aaron Rodgers and the closing speed of Troy Polamalu. But if you’re looking to capitalize on a friendly Super Bowl wager this weekend, it seems unemployment rate may be as important as anything in predicting a winner. Yes, it’s bizarre, but the team from the city with the lowest jobless rate has won 16 of the last 20 games. RiseSmart reports:

Could a city’s economic prosperity, as measured by employment level, make a difference in its team’s chances of winning the Super Bowl?  Data from the Bureau of Labor Statistics suggests that it does.  According to a new analysis by RiseSmart, the team whose metropolitan area boasts the lower jobless rate has won 16 of the past 20 Super Bowls – an 80 percent success rate.  

Based on this historical correlation, the Green Bay Packers should be the favorite to defeat the Pittsburgh Steelers in Super Bowl XLV.   Through November, the 2010 unemployment rate for the Green Bay metro area was 7.7 percent, compared to 8.1 percent for the Pittsburgh metro area. 

On January 27, 1991, the New York Giants beat the Buffalo Bills in Super Bowl XXV, despite the New York City metro area having a higher 1990 jobless rate than Buffalo.  After that game, however, the Super Bowl winning city had lower unemployment in 16 of the next 19 contests, including Super Bowl XLIV, in which New Orleans (6.7 percent 2009 unemployment) defeated Indianapolis (8.4 percent). 

Other facts of note:

  • On the six previous occasions that both teams’ metro areas have had unemployment greater than 5.5 percent — as is the case this year — the team from the metro area with the lower jobless rate has won in every instance.  

  • This is the first Super Bowl in the past two decades in which both teams hail from metro areas with jobless rates exceeding 7 percent.  On the four previous occasions that one team represented a city with 7+ percent unemployment, it lost the Super Bowl in every instance.

  • Since 1991, Super Bowl winning metro areas have had an average annual unemployment rate the prior year of 4.8 percent, compared to 5.4 percent for Super Bowl losing metro areas.

“Unemployment is the No. 1 issue in America today, and that will be true on Super Bowl Sunday as well,” said Sanjay Sathe, CEO of RiseSmart, a provider of next-generation outplacement and recruitment solutions. 

“In weighing the meaning of this analysis, correlation doesn’t imply causation, of course. But you could argue that a fan base with lower unemployment is more likely to attend games, buy team gear, celebrate at sports bars and, ultimately, cheer their team on to victory.  By contrast, a metro area that is struggling with high unemployment might have a subtle but insidious effect on its team’s morale,” Sathe said.

Super Bowl: Winner – Jobless Rate; Loser – Jobless Rate
1991: NY Giants – 5.5; Buffalo – 5.3
1992: Washington – 4.6; Buffalo – 7.2
1993: Dallas – 6.9; Buffalo – 7.5
1994: Dallas – 6.1; Buffalo – 6.8
1995: San Francisco – 5.9; San Diego – 7.1
1996: Dallas – 4.8; Pittsburgh – 6.0
1997: Green Bay – 3.4; New England – 4.1
1998: Denver – 2.9; Green Bay – 3.3
1999: Denver – 2.9; Atlanta – 3.3
2000: St. Louis – 3.5; Tennessee – 2.9
2001: Baltimore – 3.8; NY Giants – 4.4
2002: New England – 3.6; St. Louis – 4.6
2003: Tampa Bay – 5.6; Oakland – 6.2
2004: New England – 5.7; Carolina – 6.3
2005: New England – 5.0; Philadelphia – 5.1
2006: Pittsburgh – 5.2; Seattle – 5.0
2007: Indianapolis – 4.4; Chicago – 4.5
2008: NY Giants – 4.4; New England – 4.1
2009: Pittsburgh – 5.1; Arizona – 5.3
2010: New Orleans – 6.7; Indianapolis – 8.4

Note: Jobless rates are for year prior to Super Bowl year.  Source: Bureau of Labor Statistics

IU Researchers: Twitter Can Help Predict Markets

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This is just wild. According to Indiana University researchers, Twitter may be the greatest economic indicator yet: 

Researchers at IU Bloomington’s School of Informatics and Computing found the correlation between the value of the Dow Jones Industrial Average (DJIA) and public sentiment after analyzing more than 9.8 million tweets from 2.7 million users during 10 months in 2008.

Using two mood-tracking tools to analyze the text content of the large-scale collection of Twitter feeds, Associate Professor Johan Bollen and Ph.D. candidate Huina Mao were able to measure variations in public mood and then compare them to closing stock market values.

One tool, OpinionFinder, analyzed the tweets to provide a positive or negative daily time series of public mood. The second tool, Google-Profile of Mood States (GPOMS), measured the mood of tweets in six dimensions: calm, alert, sure, vital, kind, and happy. Together, the two tools provided the researchers with seven public mood time series that could then be set against a similar daily time series of Dow Jones closing values.

The researchers then correlated the two sets of values — Dow Jones and public mood — and used a self-organizing network model to test a hypothesis that predicting stock market closing values could be improved by including public mood measurements.

"We were not interested in proposing an optimal Dow Jones prediction model, but rather to assess the effects of including public mood information on the accuracy of the baseline prediction model," Bollen said. "What we found was an accuracy of 87.6 percent in predicting the daily up and down changes in the closing values of the Dow Jones Industrial Average."

Economic Club Speaker was Chided for ‘Outlandish’ Economic Predictions — That Came True

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Patrick Byrne, CEO of Overstock.com, was widely criticized by financial professionals and journalists for predicting a global financial crisis more than two years ago. Byrne, a native of Fort Wayne who received his education from Cambridge and Stanford, warned of a market meltdown perpetrated by cheap credit and writing checks on the bank accounts of future generations. The man who took Overstock.com from a half-million dollars in annual revenue to nearly $1 billion annually, takes little pleasure in accurately predicting our current economic situation but continues to advocate for what he feels are positive reforms – specifically to the controversial practice of short selling stocks.

Byrne will appear at the Economic Club of Indiana luncheon in Indianapolis on November 5. Get your tickets today.