This paper investigates whether the potential for rent extraction due to shareholders' strategic actions is reflected ex ante in stock and bond prices based on a joint study of stock and bond markets. I document that higher default probabilities are associated with higher yield spreads and bond returns but not with higher stock returns. Shareholder advantage has no significant effect on distress risk premia in stock or bond returns for firms with bonds outstanding. I also find that the negative relationship between distress risk and stock returns is more evident for firms with high trading cost and arbitrage risk. My findings suggest that the stock market, but not the bond market, misprices distress risk.

This research mainly tries to confirm the relationship between distress risk and stock returns in the Taiwan market. According to three factor theory raised by Fama-French (1992), the higher book-to-market ratio brings higher stock returns because of the higher distress risk, and also mentioned about the three significant factors in explaining expected stock return: risk, firm size, and book-to-market ratio (here replace it with price-to-book ratio). There are many studies had proved that high risk accompanies high expected stock return, but some other obtained the contrary outcome. It still depends on different characteristics of enterprises, industries, and countries. Following other researches, this paper use ¡§Z-Score¡¨ bankruptcy prediction model as the proxy of distress risk, and take the subsequent realized stock returns of the distress publicly-traded firms as a proxy of systematic risk. As it may be doubted of using Z-Score in the Taiwan stock market, this research add ¡§TCRI¡¨ to compare with. ¡§TCRI¡¨ is the credit rating score raised by Taiwan Economic Journal (TEJ). Because of the same results of rating on sample companies, it supported the application of Z-Score in Taiwan stock market. In analyzing the relationship between distress risk and stock return, this research find that firm size, distress risk and price-to-book ratio effect are significant enough to explain the expected stock return,(although distress risk and price-to-book ratio are only significant in Y-3) similar to the findings of Fazilah Samad (2009) et al. This research also found that the theoretical expectation of the size effect on distress risk does not hold in the case of the Taiwan distress publicly-traded firms, but price-to-market ratio (PB ratio) does. Unlike the findings of Fazilah Samad (2009) et al. and Griffin and Lemmon (2002), the outcome shows that there is a significant inverse relationship between PB ratio and distress risk, similar to the theory and our original expectation. It directly proved that the lower PB ratio brings higher distress risk in Taiwan market, but inconclusive to deduce that it also brings higher stock return. Meanwhile, this research tries to find out if there is a difference between distress companies and most distress companies. Besides of firm size, there is no significant difference between these two groups, and they are similar as it was closer to distress happened. Although there is not significant relationship between three factors and stock return, this study reveals the decreasing trend of financial performance among those distress firms before facing distress circumstances. It shows again that Z-Score is suitable for Taiwan market although our sample companies including manufacturing and non-manufacturing companies.

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.

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Yes / This study investigates the impact of three oil price shocks on financial distress of global firms using a dataset of 8130 firms across 48 countries from 2002 to 2022. It also analyses the role of energy diversification in the relationship between oil shocks and firm distress. The findings reveal that aggregate demand and specific demand shocks increase firm distress risk, while supply shocks reduce it. Furthermore, the results suggest that energy diversification mitigates the impact of specific demand shocks on firm distress. The study also implements several robustness checks, and the results remain consistent. Potential policy implications are also discussed.

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規模效應是資本資產定價模型所無法解釋的報酬異常現象中，最常被討論的一個。本文首先將探討台灣股市是否具有規模效應情形，若有，再進一步檢視其型態為何。接下來，本文試圖了解是否公司發生財務危機的機率高低會與規模溢酬有所關連，亦即，小公司因為較容易發生財務危機事件，因此平均而言，較大公司有更高的報酬率。本研究將採用Shumway(2001)的羅吉斯迴歸模型來估算公司發生財務危機事件之機率，並且比較不同變數之預測能力如何。 經由實證結果，發現1986年至2009年的台灣股市具有規模效應情形，此結果與之前幾位研究者之研究結果相符。而在財務危機事件機率的部份，亦可看出發生財務危機機率較高的投資組合享有較高的報酬率，此情形在小市值規模的公司身上尤其明顯。從以上發現，我們可以推論財務危機風險確實為構成規模效應的因素之一。 / Size effect is one of wildly-discussed pricing anomalies that cannot be explained by capital assets pricing model, we would like to exam whether it exists in Taiwan stock markets and how its pattern is. Furthermore, we assume the higher financial distress risk a company has, the higher expected return it will earn. That is, there is positive correlation between financial distress risk and return. Following the logistic model developed by Shumway(2001), we explore the list of variables which have greater explanatory power in prediction. Through empirical data with stocks listed and ever listed on Taiwan Stock Exchange and GreTai Securities Market, we find size effect does exist. The result is consistent with previous study. We also see firms with higher distress risk tend to have higher returns, this condition is especially obvious in small companies. So we can infer that having higher distress risk is one of the reasons why small companies can earn higher returns, they are consistent with our conjecture.

Notre thèse explore les facteurs de risque et les modèles des facteurs sur le marché boursier chinois A-share. Notre étude est basée sur le contexte du modèle facteur de Fama-French (FF). Tout d'abord, au chapitre 1, nous réexaminons l'applicabilité du Modèle Fama-French à Trois Facteurs (FF3F) et du dernier Modèle Fama-French à Cinq Facteurs (FF5F), compte tenu de plusieurs caractéristiques spéciales du marché boursier chinois. Les résultats empiriques montrent que le Modèle FF3F peut expliquer la majorité des variations de séries chronologiques des rentabilités des actions chinoises A-share. Au cours de la période d'échantillonnage, le marché bêta et le facteur SMB sont des déterminants importants pour expliquer la variation transversale des rentabilités des actions, cependant nous ne trouvons aucune prime de valeur. D’après la comparaison des performances des modèles FF3F et FF5F en présence de facteurs de rentabilité et d'investissement, le Modèle FF5F ne semble pas capturer plus de variations de rentabilités espérées que le modèle à trois facteurs, à l'exception des six portefeuilles pondérées en valeurs qui formés à partir de la taille et de la rentabilité opérationnelle.Dans le chapitre 2, nous examinons si les facteurs FF, SMB et HML, sont des proxys d'innovations de variables d'état sélectionnées (rendement de dividende agrégée, taux de T-bonds en un mois, l’écart de terme et l’écart de défaut) qui décrivent, sur la période recherche, les opportunités futures d'investissement sur le marché boursier chinois A-share. Les régressions chronologiques et les régressions des séries transversales sont réalisées sur cinq modèles comparatifs en utilisant l'approche à deux étapes Fama-MacBeth. Les facteurs FF ne perdent pas leur pouvoir explicatif, avec ou sans la présence des innovations des quatre variables d’états sélectionnées, à la fois dans les examens de séries chronologiques et les examens transversaux. Nous trouvons que l'information contenue dans l'innovation de rendements de dividende agrégés semble totalement capturée par la combinaison du marché bêta et du facteur de taille. Les facteurs FF ont pu jouer un rôle limité de capturer d'opportunités d'investissement alternatives représentées par les innovations des quatre variables d'état sélectionnées.Dans le chapitre 3, nous étudions si les facteurs FF sont des proxys de facteurs de risque de détresse et si différentes méthodes de construction des facteurs entraînent des résultats différents. Les résultats empiriques suggèrent qu'il n'y a pas de preuve significative que les facteurs FF représentent un risque de détresse sur le marché boursier chinois A-share. En comparant les résultats des régressions des séries chronologiques à partir de deux méthodes différentes, la performance du facteur de risque de détresse basé sur le DLI semble légèrement meilleure que celui basé sur le O-score. Cependant, le facteur de risque de détresse n'est pas un déterminant important des rentabilités transversales moyennes, et les facteurs FF ne peuvent pas représenter le facteur de risque de détresse dans la section transversale du marché boursier chinois A-share. / This dissertation is to explore the risk factors and factor models on Chinese A-share stock market based on the context of Fama-French (FF) factor model. First of all, chapter 1 re-examines the applicability of Fama-French Three-Factor (FF3F) Model and the latest Fama-French Five-Factor (FF5F) Model considering several special features of Chinese stock market. FF3F Model can explain a majority of time-series variation of the Chinese A-share stock returns. The market beta and SMB are important determinants in explaining the cross-sectional variation in the average stock returns over the sample period; however, we find no value premium. Comparing the performance of both FF3F Model and FF5F Model on Chinese A-share stock market, in the presence of profitability and investment factors, FF5F Model seems not capture more variations of expected stock returns than the three-factor model except the six value-weighted portfolios formed on size and operating profitability.Chapter 2 examines whether FF factors SMB and HML proxy for the innovations of selected state variables (aggregate dividend yield, one-month T-bill rate, term spread and default spread) that describe future investment opportunities on Chinese A-share stock market during the research period. Both time-series and cross-sectional regressions are performed on five comparative models using Fama-MacBeth two-stage approach. FF factors don’t lose their explanatory power with or without the presence of the innovations of selected four state variables in both the time-series and cross-sectional examinations. We find that the information contained in innovation of aggregate dividend yields seems totally captured by the combination of market beta and size factor. FF factors might have played a limited role in capturing alternative investment opportunities proxied by innovations of the selected four state variables.Chapter 3 investigates whether FF factors proxy for distress risk factor and whether different methods of constructing factors result in the different outcomes. The empirical results suggest that there is no significant evidence that FF factors are proxying for distress risk on Chinese A-share stock market. Comparing the time-series regression results by using two different methods, the distress risk factor constructed based on DLI seems to perform slightly better than that constructed based on O-score in capturing time-series average returns. However, the distress risk factor is not an important determinant of cross-sectional average returns, and FF factors cannot proxy as distress risk factor in the cross-section on Chinese A-share stock market.