Bankruptcy Events Research Articles

Simulation of the Bankruptcy Event of Companies Associated with a Business Group

Simulation of the Bankruptcy Event of Companies Associated with a Business Group

Persistence of collective memory of corporate bankruptcy events discussed on X (Twitter) is influenced by pre-bankruptcy public attention

Collective attention and memory involving significant events can be quantitatively studied via social media data. Previous studies analyzed user attention to discrete events that do not change post-event, and assume universal public attention patterns. However, dynamic events with ongoing updates are common, yielding varied individual attention patterns. We explore memory of U.S. companies filing Chapter 11 bankruptcy and being mentioned on X (formerly Twitter). Unlike discrete events, Chapter 11 entails ongoing financial changes as the company typically remains operational, influencing post-event attention dynamics. We collected 248,936 X mentions for 74 companies before and after each bankruptcy. Attention surged after bankruptcy, with distinct Low and High persistence levels compared with pre-bankruptcy attention. The two tweeting patterns were modeled using biexponential models, successfully predicting (F1-score: 0.81) post-bankruptcy attention persistence. Studying bankruptcy events on social media reveals diverse attention patterns, demonstrates how pre-bankruptcy attention affects post-bankruptcy recollection, and provides insights into memory of dynamic events.

Intergenerational bankruptcy risks: Learning from parents’ mistakes

This study investigates inter-generational transmissions of parental bankruptcy shock on children's financial behavior in adulthood. Our results show that younger children who were 9 years or below when their parents declared bankruptcy were 2–3 % points less likely to declare bankruptcy than their older siblings who were 10 years and older when the parents’ bankruptcy event occurred. We rule out alternative hypotheses, including birth order, cohort effects, and truncated sample bias. We find corroborative evidence for the “parent socialization” channel, where bankrupt parents, through interactions with children during childhood years, influence their financial behavior and reduce the risks of their children repeating the same mistakes in adulthood.

Reasons and Enlightenment for The Bankruptcy of Silicon Valley Bank

At the beginning of 2023, the 16th Silicon Valley Bank in the United States, broke out the liquidity run crisis, and then quickly declared bankruptcy, which attracted wide attention from the society. History can guide to the gains and losses, by learning bank bankruptcy cases, enterprises can better understand the importance of corporate management, financial stability and risk management and make more informed investment decisions; It can also help enterprises realize the importance of financial stability and promote relevant regulatory agencies to take measures to ensure the healthy operation of the financial system. Finally, understanding bank bankruptcy events can help relevant stakeholders know how to protect their rights and interests. This paper will conduct a deep review of the bankruptcy of Silicon Valley Bank, and will analyze the real cause of the bankruptcy of Silicon Valley Bank, hoping to help domestic and foreign banks to give corresponding enlightenment.

The Trigger and Application of Black Swan Events: A Case Study of Silicon Valley Bank Failures

On March 10, 2023, Federal regulators shut down Silicon Valley Bank, the 16th-largest bank in the country. As a result of the significant run, the bank was forced to file for bankruptcy. The purpose of this paper is to analyze the borrowing and triggering factors of black swan events by taking the Silicon Valley Bank bankruptcy event as an example, and to discuss the revelations and reflections of black swan events from the perspective of risk management based on the definition and characteristics of black swan events. Black swan events are those rare, unpredictable events with great impact, while bank bankruptcy events imply significant changes in the stability of the financial system. The failure of Silicon Valley Bank exposed the vulnerability of the banking sector and raised depositors' concerns about bank withdrawals and the cash flow crisis of global technology companies. Thus, the failure of Silicon Valley Bank has important lessons for future bank management and regulation. This paper argues that for most people, the failure of Silicon Valley Bank was not a black swan event, but even for many professionals, the impact of bank failures is unpredictable.

Bankruptcy Risk in Discounted Cash Flow Equity Valuation

We investigate the importance of bankruptcy risk in discounted cash flow (DCF) equity valuation. Our analyses first show how bankruptcy risk is incorporated in DCF valuation, where investment risk is captured by cash flow certainty equivalents. Within this general setting, we find that bankruptcy risk can be captured by discounting factors incorporating period-specific bankruptcy probabilities, allowing the numerators in a DCF valuation model to follow a binary random walk. Elaborating a model of this kind, we assess the value of the equity holders’ limited liability right (the equity holders’ right to hand over the firm to its creditors if bankruptcy occurs). Two valuation models commonly used in academic research and professional practice—the Dividend Discount Model (DDM) and the Residual Income Valuation (RIV) model—are addressed specifically. Our analyses show that bankruptcy probabilities are important for the estimation of the value drivers in both models. Even if bankruptcy probabilities are as low as 0.02, equity values might be severely exaggerated if bankruptcy risk is ignored in DDM or RIV. In particular, this holds for firms expected to have high future growth (conditioned on firm survival). For the RIV model to properly capture bankruptcy risk, we identify “bankruptcy event accounting principles” and an additional term that must be included in the model. We also show that bankruptcy risk under certain conditions can be handled through a specific calibration of the discounting rate/-s in all DCF models, allowing the value drivers—i.e., future dividends or residual income—to be forecasted conditioned on firm survival.

Machine Learning for Bankruptcy Prediction in the American Stock Market: Dataset and Benchmarks

Predicting corporate bankruptcy is one of the fundamental tasks in credit risk assessment. In particular, since the 2007/2008 financial crisis, it has become a priority for most financial institutions, practitioners, and academics. The recent advancements in machine learning (ML) enabled the development of several models for bankruptcy prediction. The most challenging aspect of this task is dealing with the class imbalance due to the rarity of bankruptcy events in the real economy. Furthermore, a fair comparison in the literature is difficult to make because bankruptcy datasets are not publicly available and because studies often restrict their datasets to specific economic sectors and markets and/or time periods. In this work, we investigated the design and the application of different ML models to two different tasks related to default events: (a) estimating survival probabilities over time; (b) default prediction using time-series accounting data with different lengths. The entire dataset used for the experiments has been made available to the scientific community for further research and benchmarking purposes. The dataset pertains to 8262 different public companies listed on the American stock market between 1999 and 2018. Finally, in light of the results obtained, we critically discuss the most interesting metrics as proposed benchmarks for future studies.

Yes Bank Crisis- A Critical Analysis on Causes, Effects & Recommendations

This paper looks at the failure of Yes Bank Ltd as the Crisis case in Indian history and the events that followed by the regulator. The first part of the paper reviews factors that led to the failure, consequently the bankruptcy events, and also the role of RBI in the survival of the Bank. The Banking Sector Regulator (RBI) has taken over the Management of a new generation private bank, Yes Bank due to the failure of Yes Bank. Interestingly, the bank was set up by top-notch professionals and it was running its operation as the 5th largest private lending bank in India. Suddenly, the RBI found such type of discrepancies in the operations of Yes Bank, through which the bank was going to be declared insolvent, and got a new life from the RBI. Such a bank was facing very critical governance issues and practices in the last 2-3 years which have led to a steady decline in the bank’s performance.

Корпоративна соціальна відповідальність бізнесу в умовах війни в Україні: національний і глобальний виміри

The article studies the features of corporate social responsibility (CSR), which were formed in face of the challenges of the war between Russia and Ukraine, resulting in humanitarian and socioeconomic problems. The Russian-Ukrainian war changed the reality of life, including economic activities, which manifested itself in a decline in economic operation of enterprises, bankruptcy events, rising unemployment, a decrease in the level of income of the population. In this regard, the article defines the role and importance of CSR in the context of war for the economy of Ukraine. The article examines the main manifestations of CSR and its modifications in both the national and the global dimensions in the new realities that subsequently have formed new directions and criteria such as financial assistance, humanitarian aid to the population; support with medicines, medical equipment and medical services; assistance in evacuation and accommodation of the population from areas of active hostilities; organization of shelter facilities for the population; assistance to the Armed Forces of Ukraine and territorial defense; payment of taxes in advance; information campaign to spread the truth about the war; promoting staff retention; business relocation; IT support in form of providing free access to information resources. It is also important for the company to be aware of the responsibility to employees and partners who continue to work, often changing their usual duties and switching to work 24/7. At the same time, attraction, focus on human capital, corporate volunteering have become the principles of CSR of business. The development of CSR against the challenges of war contributes to social sustainability. To strengthen the cohesion of Ukrainian society, it is proposed to develop such CSR practices as: social marketing, corporate volunteering; social sponsorship; social entrepreneurship; social investments, which in wartime conditions acquire special importance and form a positive image of business in accordance with new social values.

Bankruptcy, overlapping directors, and bank loan pricing

Using a sample of loan facilities borrowed by firms that share directors with bankrupt firms, this study investigates whether the overlapping directors are a transmission channel of the bankruptcy contagion effect in the bank loan market and, if so, what the underlying mechanism is. We find that firms are charged higher loan spreads in the period following the bankruptcy filing of a firm with a common director and that overlapping directors are a relevant channel for the bankruptcy contagion effect, in addition to other channels identified in literature. We also find that the negative contagion effect on loan pricing is most likely driven by the overlapping directors' reputation loss due to their involvement in bankruptcy events, and not by competing hypotheses, such as director distraction and director career concern/experience. Further analyses reveal that the adverse contagion impact on loan spreads is more pronounced when overlapping directors have greater influence over corporate policies or when their reputation is more seriously damaged. Meanwhile, the contagion effect is mitigated when interlocked firms have a higher-quality board. These results further support our evidence of the director reputation loss hypothesis. We strengthen the identification strategy to establish causality. In sum, our study identifies common directors as a channel of bankruptcy contagion effects on loan pricing and director reputation loss as an underlying mechanism.

Bankruptcy risk dependence structure using the INAR model comprising macroeconomic indicators applied to stress tests

In this study, we examined the types of bankruptcy risk dependence structures of Japanese firms. We classified bankruptcy events observed in Japan into multiple event types based on industry type and then used a multidimensional Hawkes process, which has been gaining attention recently in the field of finance research, to model the self-exciting and/or mutually exciting properties of bankruptcy among the event types. For the estimation of the intensity processes associated with the multidimensional Hawkes process, in addition to the analysis by Embrechts and Kirchner (Quantitative Finance 17:571–595, 2016) using the integer-valued auto-regression (INAR) model, we tested a new approach using the INAR model comprising macroeconomic indicators. Subsequently, we compared and considered the estimation results of the two specifications and demonstrated that the INAR model comprising macroeconomic indicators is better than the INAR model lacking macroeconomic indicators in terms of estimating the intensity process. Further, we demonstrated the effectiveness of the model from a practical perspective, with applications to stress tests.

Research on internal risk control system of P2P network lending

With the emergence of the new regulatory model, various P2P problem platforms emerge in endlessly, and the bankruptcy events continue to break out, causing investors to suffer great losses, also affecting the sound development of the P2P network lending industry. The platform system is taken as an example to analyse the internal control problems existing in the system itself, and based on this, it analyses the risks existing in the P2P industry. It is intended to start with the top-level design of risk management control, combining third-party ratings, guarantee institutions and fund custody, other factors to optimise the internal control risk of the online lending platform, so as to strengthen the platform's own information intermediary function, improve the information disclosure mechanism, and resist the risk defence capability, and look forward to the good development of this emerging industry of internet finance.

Multi-period mean-semi-entropy portfolio management with transaction costs and bankruptcy control

This study investigates a multi-period portfolio management problem under fuzzy settings. For the first time, the newly proposed semi-entropy in the literature is employed as an efficient downside risk measure for risk control in multi-period portfolio optimization. Fuzzy techniques for financial modeling show advantageous performance when future financial market conditions cannot be effectively detected with only historical data. We describe the assert returns by fuzzy variables. Two realistic constraints of transaction costs and bankruptcy events are taken into consideration in our model formulation of a multi-period mean-semi-entropy optimization program. The formulated program is rewritten as a crisp single-objective nonlinear programming by introducing a risk-aversion factor, and final solution to the program is obtained by using genetic algorithm. For the demonstration of computational results, we provide a numerical example with real-life stock data, which illustrates the main modelling concept and the efficiency of genetic algorithm solving method. Comparative analyses over several baseline models show the advantages of adopting fuzzy semi-entropy as an efficient downside risk measure for multi-period portfolio investment optimization.

Bankruptcy Prediction Analysis of PT Garuda Indonesia Compared to Four Airlines Companies in Asia

Airline industry is one of the promising industry for investors, it considered a big deal as it predicted to grow rapidly during for the next 20 years. Asia Pacific forecasted as the main player for airline in 2034, which will surpass Europe and North America. SKYTRAX Global Airlines Awards 2018 are announced Garuda Indonesia as one of the top ten best airlines in the world and the Best Cabin Crew in the world. The awards are followed by the other airlines in Asia. Nevertheless, airline industry also known for its volatility business, due to the big amount of operating cost, such as unstable fuel price and the high cost of labor. Those issues affect Indonesia’s best airlines, Garuda Indonesia, experienced loss for the past 5 consecutive years. The purpose of this research is to predict the bankruptcy possibilities of PT. Garuda Indonesia compared to five listed airlines company in Asia, which included as the best airlines in the world. This research will also analyze the relationship of Altman Z”-Score between PT. Garuda Indonesia to other companies by using Coefficient Correlation method. This research will be conducted by using Revised Altman Z” Score for non-manufacturers company which will predict the bankruptcy event for the next two or three years. The sample of this research are Garuda Indonesia (GIAA), Singapore Airlines (SING), THAI Airways (THAI), All Nippon Airways (ANA), and EVA Air (EVA) during the period of 2014-2018. Altman Z”-Score indicates that GIAA, THAI, and EVA predicted to bankrupt, while SING and ANA are predicted to be in the grey zone for the next 2 – 3 years.
 Keywords: Airline Industry, Bankruptcy, Asia, Garuda Indonesia, Altman Z-Score

Predictive Capability of Financial Ratios for Forecasting of Corporate Bankruptcy

Bankruptcy of a business firm is an event which results substantial losses to creditors and stockholders. A model which is capable of predicting an upcoming business failure will serve as a very useful tool to reduce such losses by providing warning to the interested parties. This was the main motivation for Beaver (1966) and Altman (1968) to construct bankruptcy prediction models based on the financial data (Deakin 1972). This research study also initiated with a great interest on this subject to investigate the predictive capability of financial ratios for forecasting of corporate distress and bankruptcy events. This study is expounded on similar previous studies by Altman (1968), Ohlson (1980), Beaver (1966) by examining the effectiveness of financial ratios for predicting of corporate distress. The logistics regression analysis (LRA) statistical method is used to scan the risk factors from the previous financial year data and prediction models are constructed which can reasonably classify the expected bankruptcy group and can reasonably predict the solvency status of a firm. The research has been focused on the USA companies only. A set of bankrupted and non-bankrupted company financial data are used for constructing the bankruptcy prediction model and then a second set of bankrupted and non-bankrupted company financial data has been used to test the classification accuracy of the constructed models. The result of this study is consistent with the previous bankruptcy prediction researches outcomes. This study also investigates the time factor implication of bankruptcy prediction models using 5 years financial ratios. Like other research projects this project is not without certain limitations and weaknesses. The bankrupted company data collection and compilation was a great challenge due to most of the bankrupted companies cease to operate or cease to be existed. Thanks to the great treasure of Mergent online database which facilitated collection of bankrupted company data. In order to facilitate identifying and collecting bankrupted company data, it is presumed that the companies which show as inactive status in Mergent online database are distressed or bankrupted companies. Another practical obstacle was the functionality of SPSS software and the output interpretation of the SPSS software; I used Andy Field’s “Discovering Statistics using SPSS” book to decipher the statistical jargons and to formulate the bankruptcy equations. Our constructed prediction model cannot be used universally as the study depended upon exclusively on US firm’s financial data, therefore the constructed prediction model can proved to be very useful tool for the US financial analysts and turnaround specialists to identify the distressed firms. In the case we need to use this model in other geographical location, the coefficients of the predictor variables must be re-estimated using the particular country’s financial data.

Local Bankruptcy and Geographic Contagion in the Bank Loan Market*

Abstract We examine whether corporate bankruptcies influence bank loan characteristics of geographically proximate firms. Controlling for industry contagion and local economic conditions, firms headquartered near a bankruptcy event experience a 7 basis point increase in loan spreads. The effect is transitory and cannot be fully explained by local correlated information or lenders’ financial health. Instead, the effect is more pronounced for informationally opaque bankruptcies and borrowers, and weakened among loans with relationship lenders and lenders with significant local presence.

The Quality of Bankruptcy Data and its Impact on the Evaluation of Prediction Models: Creating and Testing a German Database

This study assesses the impact of the quality of bankruptcy data on the estimation and evaluation of bankruptcy prediction models. To meet this objective, we develop a systematic methodology to obtain bankruptcy information from corporate news releases and public sources. Then, applying this methodology to the German market, we create a bankruptcy database that includes a higher number of and more accurate bankruptcy events as well as more accurate bankruptcy dates than those in the frequently used databases of Bureau van Dijk and Compustat Global. We use our bankruptcy data to conduct two empirical analyses. First, using our more accurate database, we compare the performance of several bankruptcy prediction models in the context of Germany. Second, we compare our database with Bureau van Dijk data and find that the quality of bankruptcy data significantly affects the parameter estimates and the out-of-sample evaluation of bankruptcy prediction models. Therefore, we suggest revising evidence presented by bankruptcy studies that use inaccurate bankruptcy information.

The Asymmetric Effect of Bankruptcy Fraud in Sweden: A Long-Term Perspective

ObjectivesThe knowledge of the effects of white-collar crimes is incomplete. In the article, we operationalize white-collar crimes as bankruptcy frauds. Economic models maintain that interlinkages between firms may give ‘domino effects’: bankruptcy events could lead to ‘bankruptcy chains’ in which a bankruptcy spreads to other firms. Analogously, criminologists assert that social and economic networks can be a major source of fraud diffusion, with the potential to drive other firms bankrupt. Recent empirical results show that crimes may have detrimental and even asymmetric (nonlinear) effects on economic activity. We analyze the diffusion and the aggregate development of bankruptcy frauds in Sweden over nearly two hundred years, specifically focusing on the relationship between bankruptcy frauds and the bankruptcy volume. We also consider linkages between bankruptcy frauds, bankruptcies, and the macroeconomic cycle.MethodsWe use long, aggregate time series, collected from several different historical and contemporary sources. Applying the recently developed cointegrating nonlinear autoregressive distributed lag (NARDL) model, we investigate whether the bankruptcy volume reacts asymmetrically to increases and decreases in bankruptcy frauds, both in the short and the long run.ResultsBankruptcy frauds reveal a causal effect on bankruptcies, showing an asymmetric (nonlinear) diffusion effect from economic frauds to the bankruptcy volume. Increases in bankruptcy frauds have a positive and significant effect on the bankruptcy volume. However, decreases in bankruptcy frauds show no significant effect. No causal relationship between the macroeconomic cycle and bankruptcy frauds is found.ConclusionsOur data and research approach demonstrate how previously generated hypotheses in both criminology and economic research on the relationship between (economic) crimes, economic activity, and the diffusion of white-collar crime can be tested at an aggregate level.

Is the Hawkes Graph Approach Applicable for Examining the Bankruptcy Risk Dependence Structure? An Empirical Analysis of Firms' Bankruptcies in Japan

In this research, we examine the types of bankruptcy risk dependence structures of Japanese firms. For this purpose, we classify bankruptcy events observed in Japan into multiple event types based on industry type and firm size and then use a multidimensional Hawkes process that has been drawing attention recently in the field of finance research so as to model the self-exciting and/or mutually exciting properties of bankruptcy among the event types. As for estimation of the intensity processes associated with the multidimensional Hawkes process, we attempt a new approach using a nonparametric estimation for piece-wise constant kernel functions, introduced by Embrechts and Kirchner (2) to effectively obtain a weighted directed graph representing the estimation result called the Hawkes graph, as well as a conventional maximum likelihood estimation for an exponentially decaying kernel function. We compare and consider the estimation results of the two specifications via visualization with Hawkes graph representations to find that the Embrechts and Kirchner's estimation is applicable for examination of bankruptcy risk contagion.

Organisational and accounting responses to bankruptcy: the case of the Ferrara Monte di Pietà (1598 and 1646)

The Monte di Pieta of Ferrara, established in 1507, played a preponderant role in the socio-economic development of Ferrara. The charitable organisation contributed to the development of a financing system addressed to poor social classes and of a financial intermediation market, becoming an intersection between supply and demand of money. The institution experienced alternating times of prosperity and crisis. Therefore, the paper aims at analysing how it responded to the bankruptcy events occurred in 1598 and 1646 in terms of governance, patrimony, informational and accounting system and control mechanisms. The results show that the reforms had different outcomes. In fact, while the first one was efficient, it wasn’t effective, leading to another bankruptcy. On the contrary, the second reform was effective but inefficient, because it prevent another bankruptcy to occur, but worsened the organisational procedures.