Found 44 article(s) for author 'Andrei Shleifer'

Diagnostic Bubbles

Diagnostic Bubbles, Andrei Shleifer, December 2018, Paper, “We introduce diagnostic expectations into a standard setting of price formation in which investors learn about the fundamental value of an asset and trade it. We study the interaction of diagnostic expectations with two well-known mechanisms: learning from prices and speculation (buying for resale). With diagnostic (but not with rational) expectations, these mechanisms lead to price paths exhibiting three phases: initial underreaction, followed by overshooting (the bubble), and finally a crash. With learning from prices, the model generates price extrapolation as a byproduct of fast moving beliefs about fundamentals, which lasts only as the bubble builds up. When investors speculate, even mild diagnostic distortions generate substantial bubbles.Link

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Europe in ‘more trouble’ than the U.S. 10 years after great recession

Europe in ‘more trouble’ than the U.S. 10 years after great recession. Andrei Shleifer, December 4, 2018, Video, “There are signs of fragility in the economy, but Harvard Professor Andrei Shleifer the U.S. is better off today than it was in 2008. He spoke with Yahoo Finance’s Alexis Christoforous about his new book, ‘A Crisis of Beliefs: Investor Psychology and Financial Fragility’Link

 

 

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This Market Has All The Signs Of A Bubble

This Market Has All The Signs Of A Bubble. Andrei Shleifer, September 24, 2018, Audio, “Andrei Shleifer, Professor of Economics at Harvard University, discusses his new book, “A Crisis of Beliefs: Investor Psychology and Financial Fragility,” and whether we are prepared for another financial crisis. Hosted by Pimm Fox and Lisa Abramowicz.Link

 

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Andrei Shleifer at the Ratio Institute

Andrei Shleifer at the Ratio Institute. Andrei Shleifer, May 28, 2018, Video, “Andrei Shleifer is a Professor of Economics at Harvard University. On May 28th he gave a lecture in memory of Eli F. Heckscher at Stockholm School of Economics by invitation from EHFF and the Ratio Institute. In this Ratio dialogue with Ratio CEO Nils Karlson he discusses the Heckscher lecture 2018: ‘A Crisis of Beliefs: Investor Psychology and Financial Fragility’Link

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Overreaction in Macroeconomic Expectations

Overreaction in Macroeconomic Expectations. Andrei Shleifer, December 2017, Paper, “We examine the rationality of individual and consensus professional forecasts of macroeconomic and financial variables using the methodology of Coibion and Gorodnichenko (2015), which focuses on the predictability of forecast errors from earlier forecast revisions. We document two principal findings: at the individual level, forecasters typically over-react to information, while consensus forecasts exhibit under-reaction. To reconcile these findings, we combine the diagnostic expectations model of belief formation from Bordalo, Gennaioli, and Shleifer (2018) with Woodford’s (2003) noisy information model of belief aggregation.Link

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Diagnostic Expectations and Stock Returns

Diagnostic Expectations and Stock Returns. Andrei Shleifer, July 2017, Paper, “We revisit La Porta’s (1996) finding that returns on portfolios of stocks with the most optimistic analyst long term earnings growth forecasts are substantially lower than those for stocks with the most pessimistic forecasts. We document that this finding still holds, and present several further facts about the joint dynamics of fundamentals, expectations, and returns for these portfolios. We then propose a new approach to modeling belief formation and over-reaction to news that explains these facts, based on a portable psychological model of judgment by representativeness.Link

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Beliefs about Gender

Beliefs about Gender. Andrei Shleifer, December 2016, Paper, “We conduct a laboratory experiment on the determinants of beliefs about own and others’ ability across different domains. A preliminary look at the data points to two distinct forces: miscalibration in estimating performance depending on the difficulty of tasks and gender stereotypes. We develop a theoretical model that separates these forces and apply it to analyze a large laboratory dataset in which participants estimate their own and a partner’s performance on questions across six subjects: arts and literature, emotion recognition, business, verbal reasoning, mathematics, and sports.Link

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Bubbles for Fama

Bubbles for Fama. Robin Greenwood, Andrei Shleifer, November 2016, Paper, “We evaluate Eugene Fama’s claim that stock prices do not exhibit price bubbles. Based on US industry returns 1926-2014 and international sector returns 1986-2014, we present four findings: (1) Fama is correct in that a sharp price increase of an industry portfolio does not, on average, predict unusually low returns going forward; (2) such sharp price increases do predict a substantially heightened probability of a crash; (3) attributes of the price run-up, including volatility, issuance, book-to-market ratio, market P/E ratio and the price path of the run-up can all help forecast an eventual crash; and (4) some of these characteristics can help investors earn superior returns by timing the bubble. Results hold similarly in US and international samples.Link

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A Real Estate Boom with Chinese Characteristics

A Real Estate Boom with Chinese Characteristics. Edward Glaeser, Andrei Shleifer, October 2016, Paper, “Chinese housing prices rose by over 10 percent per year in real terms between 2003 and 2014, and are now between two and ten times higher than the construction cost of apartments. At the same time, Chinese developers built 100 billion square feet of residential real estate. This boom has been accompanied by a large increase in the number of vacant homes, held by both developers and households. This boom may turn out to be a housing bubble followed by a crash, yet that future is far from certain. The demand for real estate in China is so strong that current prices might be sustainable, especially given the sparse alternative investments for Chinese households, so long as the level of new supply is radically curtailed.Link

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