Gary N. Smith

Professor Gary Smith has a long history of research projects debunking dubious uses of data in statistical analysis. His book Standard Deviation: Flawed Assumptions, Tortured Data, and Other Ways to Lie with Statistics, which was a London Times Book of the Week, warns of the dangers of confusing correlation with causation in statistical analysis. His paper "The Baseball Hall of Fame is Not the Kiss of Death" looks at the problems with searching for patterns in sports data.

He has written extensively on financial topics, with research that often shows surprising results, such as the following:

• stocks with clever ticker symbols beat the market,
• stocks going out of the Dow Jones Industrial Average generally outperform the stocks that replace them,
• the stocks with the most optimistic earnings forecasts typically do worse than the stocks with the most pessimistic earnings forecasts, and
• stocks that make Fortune’s most-admired list beat the market, but the stocks that were chosen by Good to Great and In Search of Excellence do not.

His statistical and financial research has been featured in various media, including the New York Times, Wall Street Journal, Wired, NPR Tech Nation, NBC Bay Area, CNBC, WYNC, WBBR Bloomberg Radio, Silicon Valley Insider, Motley Fool, Scientific American, Forbes, MarketWatch, MoneyCentral.msn, Newsweek, Fast Company, OZY and BusinessWeek.

He is the author of 15 books, more than 100 academic papers, and seven software programs on economics, finance and statistics. In addition to teaching at Pomona College, he also provides expert analysis and economic consulting.

His book, Money Machine, is intended to help investors distinguish between valuable financial advice and misleading, misguided and nonsensical assertions. The AI Delusion (Oxford University Press 2018) argues that, in the age of Big Data, the real danger is not that computers are smarter than us, but that we think computers are smarter than us and therefore trust computers to make important decisions for us. The 9 Pitfalls of Data Science (Oxford University Press, 2019, co-authored with Jay Cordes and winner of the PROSE award for Excellence in Popular Science & Popular Mathematics) is a compilation of grand successes and epic failures that are intended to help data scientists be more effective. The Phantom Pattern Problem: The Mirage of Big Data (Oxford University Press, 2020, co-authored with Jay Cordes) argues that we are hard-wired to notice patterns and to think that the patterns we notice are meaningful. This pattern-recognition ability served our distant ancestors well but, in this age of Big Data, patterns are inevitable, usually coincidental, and often misleading.

You can read Professor Smith's commentary on economics, business, sports and politics on his web page.

Professor Gary Smith's class and research website

Selected Publications

With Jay Cordes, The Phantom Pattern Problem: The Mirage of Big Data (Oxford University Press, 2020)

With Jay Cordes, The 9 Pitfalls of Data Science (Oxford University Press, 2019). Translated into simplified Chinese for sale in mainland China.

The AI Delusion (Oxford University Press, 2018). Translated into Chinese for sale in Taiwan, simplified Chinese for sale in mainland China, Korean and Vietnamese.

The Money Machine: The Surprisingly Simple Power of Value Investing (Amacom Books (American Management Association, 2017)

What the Luck? The Surprising Role of Chance in Our Everyday Lives (New York: Overlook, London: Duckworth. 2016). Translated into Chinese.

Essential Statistics, Regression, and Econometrics, Second edition (Academic Press, 2015)

Standard Deviations: Flawed Assumptions, Tortured Data, and Other Ways to Lie with Statistics (The Overlook Press, 2014)

With Margaret H. Smith, Houseonomics (Financial Times/Prentice Hall Books, 2008)

“The Chinese Real Estate Bubble,” with Wesley Liang, Real Estate Finance, 36(4), 2020, 239-247.

“Be Wary of Black Box Trading Algorithms,” Journal of Investing, 28 (5), 2019, 7-15.

“The Principal Problem with Principal Components Regression,” with Heidi Margaret Artigue, Cogent Mathematics & Statistics, 6 (1), 2019.

“The Name Game: The Importance of Resourcefulness, Ruses, and Recall in Stock Ticker Symbols.” with Naomi Baer and Erica Barry, Quarterly Review of Economics and Finance, 2019.

“Hurricane Names: A Bunch of Hot Air?,” Weather and Climate Extremes, 12, 2016, 80-84.

“Great Companies: Looking for Success Secrets in All the Wrong Places,” with Gabrielle Baum, Journal of Investing, 24 (3), 2015, 61-72..

“Like Mother, Like Daughter?: An Economic Comparison of Immigrant Mothers and Their Daughters,” with Margaret Hwang Smith, International Migration, 51, 2013, 181-190.

“Poker Player Behavior After Big Wins and Big Losses,” with Michael Levere and Robert Kurtzman, Management Science, 55 (9), 2009, 1547-1555.

“Would a Stock By Any Other Ticker Smell as Sweet?,” with Alex Head and Julia Wilson, Quarterly Review of Economics and Finance, 49 (2), 2009, 551-561.

“The Real Dogs of the Dow,” with Anita Aurora and Lauren Capp, The Journal of Wealth Management, 10 (4), 2008, 64-72.

“Bubble, Bubble, Where’s the Housing Bubble?,” with Margaret Hwang Smith, presented at the Brookings Panel on Economic Activity, March 30-31, 2006; subsequently published in Brookings Papers on Economic Activity, 2006: 1, 1-50.

“A Great Company Can be a Great Investment,” with Jeff Anderson, Financial Analysts Journal, 62 (4), 2006, 86-93.

“Shrunken Earnings Predictions are Better Predictions,” with Margaret H. Smith and Manfred Keil, Applied Financial Economics, 14, 2004, 937-943.

“Bowlers’ Hot Hands,” with Reid Dorsey-Palmateer, The American Statistician, 58, 2004, 38-45.

“Scared to Death?,” British Medical Journal, 325, 2002, 1442-1443.

“Regression to the Mean and Football Wagers,” with Marcus Lee, Journal of Behavioral Decision Making, 15, 2002, 329–342.

“The Nifty-Fifty Re-Revisited,” with Jeff Fesenmaier, Journal of Investing, 11, 2002, 86–90.