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In sharp contrast to the basic risk-return assumption of theoretical finance, the empirical evidence shows that distressed firms underperform non-distressed firms (e.g. Dichev, 1998; Agarwal and Taffler, 2008b). Existing literature argues that a shareholder advantage effect (Garlappi and Yan, 2011), limits of arbitrage (Shleifer and Vishny, 1997) or gambling retail investor (Kumar, 2009) could drive the underperformance. Herein, I test these potential explanations and explore the drivers of distress risk. In order to do so, I require a clean measure of distress risk. Measures of distress risk have usually been accounting-based, market-based or hybrids using both information sources. I provide the first comprehensive study that employs a variety of performance tests on different prediction models. My tests are based on all UK non-financial firms listed in the Main market segment of the London Stock Exchange (LSE) between September 1985 and October 2010. It includes 22,217 observations with 2,428 unique firms of which 202 went bankrupt. I find that hybrid models clearly outperform the accounting-based z-score (Taffler, 1983) and the market-based model of Bharath and Shumway (2008) (BS). Hybrid models forecast bankruptcies more accurately and they subsume the bankruptcy related information of z-score and BS. While there is little to distinguish between the hybrids in forecasting accuracy, tests of differential misclassification costs show that the highest economic value is delivered by the most parsimonious hybrid model of Shumway (2001) (Shum). The forecasting accuracy between z-score and BS depends on the sample period while both carry complementary bankruptcy related information. My study provides confirmatory evidence on the puzzling negative distress risk premium. Moreover, my tests show that the distress risk premium is independent of the distress risk proxy (Shum, z-score or BS). Remarkably, z-score –the weakest bankruptcy prediction model - subsumes the return related information of Shum and BS in cross-sectional tests suggesting that it might not be distress risk per se that is priced. My results provide no evidence that the potential explanations in the existing literature are able to account for the distress puzzle. As such, I find no confirmation for the shareholder advantage effect. Although the characteristics of firms with high limits of arbitrage and gambling features are shared by distressed firms, tests provide no evidence for their pricing relevance or their impact on the distress risk premium. This is the first study that deconstructs the distress measures into their component parts to unravel the distress risk premium and shows that the profitability components of Shum and z-score drive the premium. The composite measure without the information carried by profitability is insignificant in the pricing tests. In time-series regressions, I show that the pricing information carried by a profitability factor is able to reduce the distress risk premium. Portfolio analysis identifies low distress risk-high profitability firms as the key driver of the mispricing. The distress anomaly is not driven by distress risk but by profitability. Another major contribution is the use of the three approaches to assess distress risk. Together with the full range of major performance measures, I provide the first comprehensive test of the competing approaches. This study has important implications for the future research agenda on both, how we measure distress risk and the pricing of distress risk.

This thesis investigates the anomalous underperformance of distressed stocks in the US computer and electronics industry. It shows that such anomaly can be explained by a parallel analysis of risk based rational pricing and profitability (earnings) levels to returns relationship propositions. For the 1990 to 2006 period, distressed stocks have on average underperformed their non-distressed counterparts. However, once the conditional relationship with profitability is taken into account, the distress risk is rewarded by a continuous positive return hence priced appropriately. In the computer and electronics industry growth stocks (low B/M) outperform on average value stocks (high B/M). The size factor has not been confirmed to be significant in explaining stock returns for this specific industry over the 1990 to 2006 period. The study also reveals that B/M and size factors do not proxy for distress risk. The B/M factor follows an inverted u-shape along the distress risk deciles axis. As result, stocks in low and high distress portfolios share similarly low B/M values. Cash flow based bankruptcy predictors estimated on a quarterly basis from a Cox proportional hazard model, that are used as proxy for a continuous distress risk factor in asset pricing tests, are able to predict bankruptcies at higher accuracy rates than the Z-Score as alternative measure.

This doctoral submission represents over ten years of focused research that has resulted in a unique collection of academic and professional articles. The epithet "unique" is adopted to reflect that over those years this area of study has been relatively untouched by other academic researchers. This submission presents a total of eight academic and seven professional journal publications that chronicle the major output of numerous research projects undertaken between 1992 and 2002. The publications adhere to a central aim - to investigate the practical use and complex interactions between stakeholders of the individual insolvency rescue vehicle the Individual Voluntary Arrangement (IVA). The research projects employed a variety of relevant methodologies to populate an emerging conceptual model of the prime factors affecting the incidence, usage and outcomes of IVA cases. The first five articles report and develop the data collected during the various projects. The articles build on each other, analysing results and comparing these with previous studies to underline reliability in the data. The final three articles draw threads from the research data and develop the conceptual model further. As a research progression this submission contains all of the necessary ingredients of a doctoral thesis. It focuses on a discrete body of knowledge, builds on a conceptual model, gathers valuable data and tests it, draws strong conclusions and, finally, establishes and contributes new theory in this area of study.