The Role of Debt in an Insolvency Proceeding Abstract The thesis aim's to analyze the process of claims in a broader sense: from the filing of the claim, through its review by the insolvency court and the insolvency administrator, to (in the most ideal case) the satisfaction of creditors. The thesis deals with the issues of the claims process and the claims themselves. The analysis of the topic is based mainly on the applicable legislation, current case law, the opinions of professionals in professional articles, and a questionnaire survey. Insolvency law is an essential part of the legal system as it reflects the current economic state of modern society. The topic is topical because the field of insolvency law is constantly being amended, one of the sources of these amendments being changes in social conditions. The legislator aims to make the institution of debt settlement available to a wider range of debtors through amendments to the Insolvency Act and thus reintegrate them into economic life as soon as possible. The thesis is divided into four chapters. The first chapter deals with the description of individual types of claims and their breakdown. The remaining chapters follow the claims process. The second chapter describes the application of claims, including the form and requirements of a claim...

Studying household finance and behavior is important not only for understanding the micro level behavior, but also to have a better understanding of the whole economy. The study of household behavior become even more important after the 2007 housing crises, and the giant effect it had (and is still having) on Wall Street and the whole US and global economy. This dissertation is an attempt to understand some of the household behavior: how does the new internet era affect the demand for credit cards, which attitudes influence the household's decision to file bankruptcy, and whether expenditure habits encouraged overspending. The study will use the micro level data provides by Survey of Consumer Finance SCF2007. In the first chapter, the study focuses on the effect of having internet access on household demand for credit cards, controlling for standard price, income effects and other financial and demographic variables. The internet changed the way consumer shops, with more information about the product, the market and the price. E-Commerce retail sales grew on average of 22% a year over the past decade; in the second quarter of 2009 it reached $32.4 billion. The study found that households who have access to the internet, carry around $862 more on their credit card balance, in average, than households who have no access to the internet. The second chapter investigates the effects of borrowing and saving attitudes on household decision to file for personal bankruptcy. The total non-commercial bankruptcy filings increased from 560,682 cases in 2006 to 784,079 in 2007. This increase continued through 2008 and the first quarter of 2009, with 1,031,443 cases filed in 2008 and 304,228 in the first three months of 2009. The study results suggest that borrowing and saving attitudes have no effect of household decision to file for bankruptcy except for paying credit card balance in full every month. The third chapter studies the relationship between eating out "Food-Away-From-Home" and overspending. Since 19% of household in the US are spending more than their income. The average for the past nine years (2000-2008) was 1.6%. Compared to other industrialized countries, the US had one of the worst personal saving rates during the past twenty years . The study found that eating out does not encourage overspending. On the contrary, the higher the ratio of FAFH to total food expenditures the less likely household will overspend.

We study the impacts of bankruptcy risk on the performance of market-based pollution control policies. In chapter one, we concentrate on emissions trading markets. We find that firms that risk bankruptcy demand more permits than if they were financially secure. Thus, bankruptcy risk in a competitive market for tradable permits causes an inefficient distribution of these permits among firms. Moreover, the equilibrium distribution of permits is dependent on the initial allocation of permits. Thus, the main reasons for implementing emissions trading markets do not hold when some firms are financially insecure. In fact, the inefficiency that is associated with bankruptcy risk is worsened if financially insecure firms are given a smaller share of the initial allocation of permits. In chapter two, we investigate the influences of bankruptcy risk on imperfectly enforced emissions taxes. Under favorable, but not unrealistic conditions, an imperfectly enforced emissions tax produces an efficient allocation of individual emissions control; the aggregate level of control is the same whether enforcement of a tax is sufficient to induce the full compliance of firms or not, and differences in individual violations are independent of firm-level differences. All of these desirable characteristics disappear when some firms under an emissions tax risk bankruptcy—the allocation of emissions control is inefficient, imperfect enforcement causes higher aggregate emissions, and financially insecure firms choose higher violations.

This dissertation examines the social construction of American federal bankruptcy law from the Gilded Age to the post-World War II Era. Across the nineteenth century, federal legislators vociferously debated whether a federal bankruptcy statute would facilitate the extension of business credit across state lines or be employed by creditors to oppress small traders, farmers, and wage earners. After the law’s enactment in 1898, however, this debate largely disappeared. By the period following the Second World War, bankruptcy was an accepted means for working class debtors to obtain debt relief, either immediately or after paying their creditors out of their future wages. Across four chapters, I explore the factors associated with this shift. How did bankruptcy become an accepted part of the American political economy and welfare state? To answer these questions, I analyze new samples of census-linked bankruptcy petitions in comparison with survey data on working class debtors, a corpus of Congressional speech and media, and archival data on relevant policy actors. Social reformers’ efforts to create “fair” credit markets through Small Loan Laws (SLL), alongside rising bankruptcy rates, ultimately naturalized a conception of bankruptcy as morally “caused” by debtors, apart from creditor choices or malfeasance. As SLLs reduced real interest rates, they also led lenders to collateralize their relative risks through extending credit in states where it was legal to garnish debtors’ wages. In doing so, SLLs inadvertently spurred credit extension based on wages rather than property. The conception that debtors “caused” bankruptcy, in turn, led Great Depression Era legislators to focus on delineating who was “deserving” of bankruptcy protections and how insolvent individuals could prove their future “creditworthiness” and reenter financial markets. The 1938 Bankruptcy Act established a voluntary wage-earner payment system (Chapter XIII) for “deserving” white men while also formalizing provisions for immediate debt discharge (Chapter VII). Yet when few wage earners decided to “honorably” pay their debts over time, judicial actors in post-World War II America employed Chapter XIII bankruptcy as a debt collection system that reduced lenders’ risks against “undeserving” bankrupts. As Black people increasingly sought debt relief through bankruptcy protections, they were directed to Chapter XIII, irrespective of their economic interests. These payment plans increased the time and money that Black bankrupts needed to pay in order to regain their economic citizenship.

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My dissertation consists of two chapters which explores various aspects of empirical corporate finance and institutional ownership. In the first chapter, I examine whether common owners – an institution with holdings in both the distressed and the lending firm – ameliorates this conflict given that common owners should seek to maximize the equity value of both firms. The results show that when a common owner holds a stake in both the borrowing and lending firm, distressed firms are over 3.3-times more likely to file for Chapter 11 freefall bankruptcy (rather than prepack) as compared to borrowing-lending firms without a common owner. Using ownership of passive funds as an instrument for the presence of a common owner, I provide evidence of a causal relation between common ownership and bankruptcy filing choice. Overall, the analysis indicates that common ownership in both financially distressed borrowing firms and their lending firms leads to a greater likelihood of Chapter 11 freefall bankruptcy filing; suggesting that common owners typically side with creditors to maximize their combined equity value in both the borrowing and lending firm. Next, I examine the effect of CEO social connections on stock returns. An equally weighted (value weighted) long-short portfolio strategy earns investors excess returns of 5.39% (4.44%) per year. Three potential reasons explain the relation between CEO social connections and excess returns; better firm performance, investor information asymmetry, and/or greater investor risk-bearing. Our analysis provides evidence consistent with CEO connections both increasing firm risk and improving firm performance. / Business Administration/Finance

Since Altman’s 1968 discriminant analysis model for corporate bankruptcy prediction, there have been numerous studies applying statistical and machine learning (ML) models in predicting bankruptcy under various contexts. ML models have been proven to be highly accurate in bankruptcy prediction up to three years before the event, more so than statistical models. A major limitation of ML models is that they suffer from an inability to handle highly imbalanced datasets, which has resulted in the development of a plethora of oversampling and undersampling methods for addressing class imbalances. However, current research on the impact of different sampling methods on the predictive performance of ML models is fragmented, inconsistent, and limited. This thesis investigated whether the choice of sampling method led to significant differences in the performance of five predictive algorithms: logistic regression, multiple discriminant analysis(MDA), random forests, Extreme Gradient Boosting (XGBoost), and support vector machines(SVM). Four oversampling methods (random oversampling (ROWR), synthetic minority oversampling technique (SMOTE), oversampling based on propensity scores (OBPS), and oversampling based on weighted nearest neighbour (WNN)) and three undersampling methods (random undersampling (RU), undersampling based on clustering from nearest neighbour (CFNN), and undersampling based on clustering from Gaussian mixture methods (GMM) were tested. The dataset was made up of non-listed Swedish restaurant businesses (1998 – 2021) obtained from the business registry of Sweden, having 10,696 companies with 335 bankrupt instances. Results, assessed through 10-fold cross-validated AUC scores, reveal those oversampling methods generally outperformed undersampling methods. SMOTE performed highest in four of five algorithms, while WNN performed highest with the random forest model. Results of Wilcoxon’s signed rank test showed that some differences between oversampling and undersampling were statistically significant, but differences within each group were not significant. Further, results showed that while the XGBoost had the highest AUC score of all predictive algorithms, it was also the most sensitive to different sampling methods, while MDA was the least sensitive. Overall, it was concluded that the choice of sampling method can significantly impact the performance of different algorithms, and thus users should consider both the algorithm’s sensitivity and the comparative performance of the sampling methods. The thesis’s results challenge some prior findings and suggests avenues for further exploration, highlighting the importance of selecting appropriate sampling methods when working with highly imbalanced datasets.

All firms should aim to reduce their risks and avoid bankruptcy. One way they try to lessen their chance of bankruptcy, or entering into a financially distressed state, is by using risk management techniques. Part of risk management is using derivatives, which many firms rely on today to reduce their exposure to certain types of risk and avoid a cash flow crunch. I test the notion that hedging reduces the probability of bankruptcy. Hedging reduces risks such as interest rate and currency risk, and these types of risk can send a firm into financial distress. Financial distress can result in bankruptcy, so hedging should then ultimately reduce the risk of bankruptcy.

Tyrimo objektas – įmonių finansinių sunkumų diagnozavimas. Darbo tikslas – sukurti įmonių finansinių sunkumų diagnozavimo modelį ir jį patikrinti pasirinktų įmonių pavyzdžiu. Tyrimo uždaviniai:  išanalizuoti ir susisteminti anksčiau sukurtus bankroto prognozavimo modelius ir jų testavimo rezultatus;  sudaryti įmonių finansinių sunkumų diagnozavimo modelį;  patikrinti sukurto modelio tinkamumą pasirinktų įmonių tarpe. Tyrimo metodai. Analizuojant bankroto prognozavimo modelius ir jų testavimo rezultatus atlikta mokslinės ir metodinės literatūros loginė ir lyginamoji analizė bei sintezė. Įmonių finansinių sunkumų diagnozavimo modeliui parengti skaičiuoti finansiniai santykiniai rodikliai bei atlikta statistinė analizė, rezultatai pateikti taikant monografinį metodą. Remiantis indukcijos metodu ir logine analize tikrintas sukurto finansinių sunkumų diagnozavimo modelio tinkamumas analizuotų įmonių tarpe. Tyrimo rezultatai. Pirmojoje darbo dalyje išanalizuota finansinių sunkumų esmė bei juos sąlygojančios priežastys, nustatytas finansinių sunkumų diagnozavimo būtinumas, išnagrinėti ir apibendrinti bankroto prognozavimo modeliai bei išskirti dažniausiai juose naudojami finansiniai santykiniai rodikliai. Antrojoje darbo dalyje sukurtas logistine analize paremtas finansinių sunkumų diagnozavimo modelis bei iškelta hipotezė, kad jis leidžia patikimai apskaičiuoti įmonių finansinių sunkumų tikimybę tirtų įmonių aibėje. Trečiojoje darbo dalyje sudarytas finansinių sunkumų... [toliau žr. visą tekstą] / Research object – diagnosis of company financial difficulties. Research aim - to create diagnostic model for company financial difficulties and to test it using cases of selected companies. Objectives:  to analyze and systematize previously developed bankruptcy prediction models and their test results;  to create a diagnostic model for company financial difficulties;  to analyze the relevance of the model with the selected companies. Research methods: logical and comparative analysis of scientific and methodical literature, statistical analysis, monographic method, induction method, logical analysis. Research results. The first part analyzes the financial difficulties and their underlying causes, establishes the necessity of the financial stress test model, analyzes and summarizes bankruptcy prediction models, and distinguishes the most frequently used financial ratios. The second part creates a logical analysis based diagnostic model for financial difficulties and presents hypothesis, that this model ensures reliable calculation of probability of company financial difficulties among the tested corporations. The third part uses randomly selected companies to test the created diagnostic model for financial difficulties. The developed model is suitable for the manufacturing companies, because it separates financially well standing companies from the ones that are having difficulties; however, it is not as suitable for the services and sales sector, because the model is only... [to full text]