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Predicting Financial Distress and the Performance of Distressed Stocks

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2011

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Journal of Investment Management
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Campbell, John Y., Jens Dietrich Hilscher, and Jan Szilagyi. 2011. Predicting financial distress and the performance of distressed stocks. Journal of Investment Management 9(2): 14-34.

Abstract

In this paper, we consider the measurement and pricing of distress risk.We present a model of corporate failure in which accounting and market-based measures forecast the likelihood of future financial distress. Our best model is more accurate than leading alternative measures of corporate failure risk.We use our measure of financial distress to examine the performance of distressed stocks from 1981 to 2008. We find that distressed stocks have high stock return volatility and high market betas and that they tend to underperform safe stocks by more at times of high market volatility and risk aversion. However, investors in distressed stocks have not been rewarded for bearing these risks. Instead, distressed stocks have had very low returns, both relative to the market and after adjusting for their high risk. The underperformance of distressed stocks is present in all size and value quintiles. It is lower for stocks with low analyst coverage and institutional holdings, which suggests that information or arbitrage-related frictions may be partly responsible for the underperformance of distressed stocks.

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financial distress, distress risk, corporate failure, performance of distressed stocks

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Predicting Financial Distress and the Performance… : DASH Story 2016-05-31
Thanks for making so many articles freely available to the public. I'm a strong believer in the open access model, and disappointing that more economics/finance/accounting journals do not pursue this model. Publicly funded research should be a public good.
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Predicting Financial Distress and the Performance… : DASH Story 2017-06-25
Academic journal subscriptions have gone up in price quite a bit. Meanwhile, academic libraries have become more and more distant to the general public, thus preventing an educated layman to access recent research without great cost. DASH brings current research to the masses!