Qian Li, Fengzhong Wang, Jianrong Wei, Yuan Liang, Jiping Huang and H. Eugene Stanley

Abstract

The recent financial crisis has caused extensive world-wide economic damage, affecting in particular those who invested in companies that eventually filed for bankruptcy. A better understanding of stocks that become bankrupt would be helpful in reducing risk in future investments. Economists have conducted extensive research on this topic, and here we ask whether statistical physics concepts and approaches may offer insights into pre-bankruptcy stock behavior. To this end, we study all 20092 stocks listed in US stock markets for the 20-year period 1989–2008, including 4223 (21 percent) that became bankrupt during that period. We find that, surprisingly, the distributions of the daily returns of those stocks that become bankrupt differ significantly from those that do not. Moreover, these differences are consistent for the entire period studied. We further study the relation between the distribution of returns and the length of time until bankruptcy, and observe that larger differences of the distribution of returns correlate with shorter time periods preceding bankruptcy. This behavior suggests that sharper fluctuations in the stock price occur when the stock is closer to bankruptcy. We also analyze the cross-correlations between the return and the trading volume, and find that stocks approaching bankruptcy tend to have larger return-volume cross-correlations than stocks that are not. Furthermore, the difference increases as bankruptcy approaches. We conclude that before a firm becomes bankrupt its stock exhibits unusual behavior that is statistically quantifiable.

You can read some commentary on this paper over at PhysOrg:

During the 20-year period from 1989 to 2008, 21% of of all stocks listed in US stock markets became bankrupt. Since bankruptcies affect many investors and have played a large role in the recent global financial crisis, predicting bankruptcy before it happens could help some investors avoid large losses. In a new study, a team of physicists has used concepts from statistical physics to identify some characteristic behaviors of pre-bankrupt stocks that differ significantly from stocks that don't become bankrupt. The approach may eventually help investors forecast stock bankruptcies weeks or months in advance.