Abnormal Trading Behavior Of Specific Types Of Institutional Shareholders Before Firm BankruptcyVW Staff
Abnormal Trading Behavior Of Specific Types Of Institutional Shareholders Before Firm Bankruptcy And Its Ramifications For Firm Bankruptcy Prediction
Louisiana State University
William J. Moser
May 21, 2016
Bankruptcy prediction models, like the one formulated by Campbell et al (2008), may be used by stakeholders to evaluate risks related to investing in distressed firms. This paper examines the behavior of certain groups of institutional investors (short-term, long-term, top-performing, and those with fiduciary responsibility) in the eight quarters leading up to a firm’s bankruptcy filing. Using a matched sample based on year, industry and probability of future bankruptcy, we identify groups of institutional investors that demonstrate abnormal trading behavior in these quarters. We then use this information to enhance the predictive capabilities of Campbell et al.’s (2008) bankruptcy model.
Abnormal Trading Behavior Of Specific Types Of Institutional Shareholders Before Firm Bankruptcy And Its Ramifications For Firm Bankruptcy Prediction – Introduction
The consequences of a firm’s bankruptcy for investors who fail to liquidate their interests in a timely manner prior to a bankruptcy filing is potentially catastrophic with a trend in which pre-bankruptcy shareholders lose their entire investment. While in the 1980’s pre-bankruptcy shareholders were able to recover at least part of their investment approximately 78% of the time after a firm went through the bankruptcy process (LoPucki and Whitford 1990), a more recent survey indicates that less than 10% of the pre-bankruptcy shareholders were able to recover any portion of their investment (Wood 2011). According to data provided by New Generation Research, Inc. the combined asset value of the 52 public companies that filed for bankruptcy in 2014 was $71.8 billion. The decline in recovery rate for equity holders in bankruptcy along with the potential for substantial losses makes bankruptcy a catastrophic event for shareholders.
In an effort to minimize losses, stakeholders seek accurate and timely information regarding the future prospects of firms. Academic researchers have developed increasingly more sophisticated bankruptcy predication models (Altman 1968; Merton 1974; Ohlson 1980; Shumway 2001; Campbell et al. 2008) to inform stakeholders regarding the financial condition of individual firms and predict the probability that a firm will file for bankruptcy in the future. Lennox (1999) finds that bankruptcy prediction models are generally able to outperform bankruptcy predictions based on auditor issued going concern reports. As a result, Lennox (1999) suggests that stakeholders should rely on the bankruptcy prediction models for decision making. The existing bankruptcy probability measures primarily focus on accounting financial statement information and market return data. However, each of these models ignores an important source of firm-specific information, the trading behavior of specific types of institutional investors in the quarters preceding bankruptcy. Our research seeks to extend prior research in the areas of institutional investors and bankruptcy by providing information regarding the abnormal trading behavior of various types of institutional investors in the quarters leading up to a firm’s bankruptcy filing. We then use this information to further supplement the predictive capabilities of the bankruptcy prediction model developed by Campbell et al. (2008).
Institutional investors are informed market participants, whose incentives to maximize the profits of their investment portfolios motivate them to seek and process all available information.1 Since institutional investors’ superior information processing informs their trades, Piotroski and Roulstone (2004) suggest that institutional investors’ abnormal trading provides firm-specific information to market prices. Previous research suggests that institutional investors are not a homogeneous group (Yan and Zhang 2009). As such, based on common characteristics, they can be partitioned into categories of institutional investors, some of which possess superior information processing capabilities in particular information environments (Yan and Zhang 2009). As such, we follow prior research and categorize institutional investors into four categories: (1) short-term institutional investors (Yan and Zhang 2009); (2) long-term institutional investors (Yan and Zhang 2009); (3) top-performing institutional investors (Adebambo et al. 2015); and (4) institutional investors subject to stringent fiduciary responsibility standards (Bennett et al. 2003).
We use a matched sample to determine whether or not specific categories of institutional investors have superior information processing capabilities with respect to bankruptcy prediction. Since we seek to provide a more complete picture of what institutional investor firm-specific information flows to the market in the months leading up to a firm’s bankruptcy filing, we focus on the abnormal trading behavior of each investor group. To identify abnormal trading behavior, we control for factors that have been identified by previous research as influencing institutional investors’ trading behavior. We then match a sample of firms that eventually file for bankruptcy between 1992 and 2012 with firms in the same year and industry that are equally distressed eight quarters before bankruptcy using Campbell et al.’s (2008) measure of bankruptcy risk. We find that specific types of institutional investors demonstrate trading behavior that deviates from what would be expected based on previous research in the quarters leading up to bankruptcy.
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