Extrapolation and Bubbles

Nicholas  Barberis; Robin  Greenwood; Lawrence  Jin; Andrei   Shleifer

Article | Journal of Financial Economics | August 2018

Extrapolation and Bubbles

by Nicholas Barberis, Robin Greenwood, Lawrence Jin and Andrei Shleifer

Abstract

We present an extrapolative model of bubbles. In the model, many investors form their demand for a risky asset by weighing two signals: an average of the asset’s past price changes and the asset’s degree of overvaluation. The two signals are in conflict, and investors “waver” over time in the relative weight they put on them. The model predicts that good news about fundamentals can trigger large price bubbles. We analyze the patterns of cash-flow news that generate the largest bubbles, the reasons why bubbles collapse, and the frequency with which they occur. The model also predicts that bubbles will be accompanied by high trading volume and that volume increases with past asset returns. We present empirical evidence that bears on some of the model’s distinctive predictions.

Keywords: bubble; extrapolation; volume; Price Bubble; Mathematical Methods;

Format: Print

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Citation:

Barberis, Nicholas, Robin Greenwood, Lawrence Jin, and Andrei Shleifer. "Extrapolation and Bubbles." Journal of Financial Economics 129, no. 2 (August 2018): 203–227.

On the afternoon of Monday October 13, 2008, Hank Paulson Jr., the Secretary of the Treasury of the United States, walked into the large conference room across the hall from his office in the Treasury Department. Joining him were Federal Reserve Chairman Ben Bernanke, President of the Federal Reserve Bank of New York Timothy Geithner, Chair of the Federal Deposit Insurance Corporate Sheila Bair, and the Chief Executive Officers of nine of the largest banks in the United States. This distinguished group had been brought together by the most serious financial crisis since the Great Depression of the 1930s. Financial panic was pushing the U.S. and European financial systems to the brink of failure. Paulson hoped his meeting with the bank CEOs would be a turning point. U.S. financial markets were closed for Columbus Day, and Paulson was planning to announce the latest government actions to stabilize the financial system before markets reopened on Tuesday.

In February and March 2009, the U.S. economy was in the midst of a terrifying financial and economic crisis. Between the beginning of 2008 and early 2009, four of the 25 largest U.S. financial institutions had failed, and nine of these 25 institutions had taken extraordinary steps to avoid failure—either receiving one-off government support, merging with another firm, or submitting to heightened regulation to qualify for future government support. Led by Treasury Secretary Timothy Geithner, the government had to quickly devise policies to stabilize the financial system and the economy. The case explores the details of policies, and the decision making process that led to them, that Geithner and his team devised under immense time pressure to stabilize the system. The case features an extended discussion of Geithner’s innovative “stress test,” which would reveal the longer-term health of the country’s largest banks.

We evaluate Eugene Fama's claim that stock prices do not exhibit price bubbles. Based on U.S. industry returns 1926–2014 and international sector returns 1985–2014, 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 predict a substantially heightened probability of a crash; (3) attributes of the price run-up, including volatility, turnover, issuance, and the price path of the run-up, can all help forecast an eventual crash and future returns; and (4) some of these characteristics can help investors earn superior returns by timing the bubble. Results hold similarly in U.S. and international samples.

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Extrapolation and Bubbles

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