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A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

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125251376501 · Jun 202019922001200920172026
48 results for Bankruptcy Prediction

Paper presents ECL dataset for multi-modal bankruptcy prediction.

problem Developing models to predict corporate bankruptcy using textual and numerical data.
method Used ECL dataset to develop and evaluate classical and neural models.
result Textual and numerical data modalities complement each other for bankruptcy prediction.

The study predicts bankruptcy in Indian companies using financial ratios.

problem Predicting early signs of corporate bankruptcy in Indian companies.
method Logistic regression considering profitability, leverage, and efficiency ratios for one and two years before bankruptcy.
result The model accurately predicts bankruptcy with 81.4% and 85.1% accuracy one and two years before filing, respectively.

Narrative disclosures in 10-K filings improve bankruptcy prediction beyond accounting ratios.

problem Traditional bankruptcy prediction models rely on accounting ratios, which may not capture early warning signals.
method Developed a PB Stress Score based on distress-specific language in 10-K narratives, evaluated against accounting and dictionary benchmarks.
result Adding the PB Stress Score increases AUC from 0.8323 to 0.9019 and improves top-decile bankruptcy capture from 44.12% to 64.71%.

Research aims to predict fallen angel bonds' bankruptcy using machine learning.

problem Predicting which fallen angel bonds will become investment grade or go bankrupt.
method Used four classification methods (logistic regression, KNN, SVM, NN) and Google Cloud's automated machine learning.
result Google Cloud's machine learning model performed best in over-sampled and feature selection data sets.

Gradient boosted trees outperform other models in predicting corporate bankruptcy.

problem Predicting financial distress of publicly traded U.S. firms.
method Benchmarked various machine learning models using a comprehensive sample of bankruptcies.
result Gradient boosted trees outperform other models in one-year-ahead forecasts.

New model uses financial filings to predict bankruptcy, even without MDA sections.

problem Lack of complete MDA data limits traditional bankruptcy prediction models.
method Conditional Multimodal Discriminative (CMMD) model learns from accounting, market, and textual data.
result Empirical results show superior classification performance compared to traditional models.

Study combines intra-risk and contagion risk for SME bankruptcy prediction.

problem Predicting bankruptcy risk of SMEs considering both intra-risk and contagion risk.
method Proposes a novel model using Graph Neural Networks to combine intra-risk and contagion risk.
result Model outperforms state-of-the-art methods in bankruptcy prediction.

New method predicts bankruptcy by imputing missing data with granular semantics.

problem Missing data, high dimensional data, and class imbalance in bankruptcy prediction.
method Granular computing for missing data imputation with feature semantics and AI-driven pipeline.
result Efficient solution for big datasets with high imputation rates.

Model predicts Mozambique bank failures, aiding risk management.

problem Lack of bankruptcy prediction model in Mozambique banking sector.
method Linear Discriminant Analysis method, using financial indicators.
result Model accurately predicted 84% of bank failures 1 year before Central Bank intervention.

New distress dictionary improves bankruptcy prediction from disclosure text.

problem Bankruptcy prediction from financial disclosures.
method Proposes a distress dictionary based on managers' sentences, quantifies linguistic features, and builds predictive models.
result Predictive models based on the distress dictionary outperform existing methods.

Paper introduces a benchmark for predicting bankruptcy from text data.

problem Lack of a common benchmark dataset and evaluation strategy for unstructured data in bankruptcy prediction.
method Describes and evaluates several baseline models, including a bag-of-words model.
result A lightweight bag-of-words model performs surprisingly well, especially when considering data from multiple years.

Proposes a new bankruptcy prediction model using Bayesian framework with expert knowledge.

problem Bankruptcy prediction using accounting ratios and statistical models.
method Generative modeling with Expert Bayesian framework.
result Model is either comparable or superior to existing methods with lower False Positive Rate.

Adapts Altman's model to compositional data for bankruptcy prediction.

problem Predicting business default using standard financial ratios has issues.
method Uses compositional data methodology with log-ratios and machine learning.
result Compositional methods improve predictive performance, especially random forests.

We have conducted an agent-based simulation of chain bankruptcy. The propagation of credit risk on a network, i.e., chain bankruptcy, is the key to nderstanding largesized bankruptcies. In our model, decrease of revenue by the loss of accounts payable is modeled by an interaction term, and bankruptcy is defined as a ca…

2007-09-27abs ↗pdf ↗

Optimizes dividend control in a bankruptcy process using a special Levy process.

problem Optimizing dividend payouts in a bankruptcy process.
method Using a non-standard spectrally negative Levy process with endogenous regime switching.
result Optimal dividend control is of the barrier type and the optimal barrier can be identified.

Interval bankruptcy problems arise in situations where an estate has to be liquidated among a fixed number of creditors and uncertainty about the amounts of the claims is modeled by intervals. We extend in the interval setting the classical results by Curiel, Maschler and Tijs (1987) that characterize division rules wh…

2013-01-07abs ↗pdf ↗

Optimal dividends strategy in a two-state regime-switching environment.

problem Maximizing profits from dividends until bankruptcy in a company with fluctuating cash surplus and regime changes in drift, volatility, and bankruptcy levels.
method Analyzes the optimal dividend payout strategy considering four factors: Brownian fluctuations in cash surplus, regime changes in drift, volatility, and bankruptcy levels.
result Rich structure of the optimal strategy, which can be either barrier-type or liquidation-barrier type, depending on model parameters.

We study a singular stochastic control problem faced by the owner of an insurance company that dynamically pays dividends and raises capital in the presence of the restriction that the surplus process must be above a given dividend payout barrier in order for dividend payments to be allowed. Bankruptcy occurs if the su…

2019-02-17abs ↗pdf ↗

Using an exhaustive list of Japanese bankruptcy in 1997, we discover a Zipf law for the distribution of total liabilities of bankrupted firms in high debt range. The life-time of these bankrupted firms has exponential distribution in correlation with entry rate of new firms. We also show that the debt and size are high…

2003-10-03abs ↗pdf ↗

We model a network economy with three sectors: downstream firms, upstream firms, and banks. Agents are linked by productive and credit relationships so that the behavior of one agent influences the behavior of the others through network connections. Credit interlinkages among agents are a source of bankruptcy diffusion…

2010-06-17abs ↗pdf ↗

This note explores the mathematical theory to solve modern gamblers ruin problems. We establish a ruin framework and solve for the probability of bankruptcy. We also show how this relates to the expected time to bankruptcy and review the risk neutral probabilities associated an adjustment to asymmetrical views.

2014-03-24abs ↗pdf ↗

We analyze the size dependence and temporal stability of firm bankruptcy risk in the US economy by applying Zipf scaling techniques. We focus on a single risk factor-the debt-to-asset ratio R-in order to study the stability of the Zipf distribution of R over time. We find that the Zipf exponent increases during market …

2010-11-11abs ↗pdf ↗

We introduce a model in which a regulator employs mechanism design to embed her human capital beta signal(s) in a firm's capital structure, in order to enhance the value of her post career change indexed executive stock option contract with the firm. We prove that the agency cost of this revolving door behavior increas…

2013-12-27abs ↗pdf ↗

The 1/3 Financial Rule helps prevent household bankruptcy through balanced spending, savings, and debt repayment.

problem Reducing household bankruptcy risk through effective financial planning.
method Mathematical modeling, game theory, behavioral finance, and technological analysis.
result The 1/3 Financial Rule emerges as a robust solution for supporting household financial stability.

Study optimal portfolio strategy with sporadic bankruptcy for isoelastic utility.

problem Maximizing expected isoelastic utility in a stock with potential bankruptcy.
method Coupled Hamilton-Jacobi-Bellman (HJB) equations, stochastic integral approach.
result Non-myopic optimal weights for non-logarithmic utilities.

The question we address here is of whether phenomena of collective bankruptcies are related to self-organized criticality. In order to answer it we propose a simple model of banking networks based on the random directed percolation. We study effects of one bank failure on the nucleation of contagion phase in a financia…

2001-11-30abs ↗pdf ↗

This study analyzes how cryptocurrency networks adapt to financial disruptions.

problem Understanding how cryptocurrency networks respond to financial crises.
method Vertex centrality measures to assess network stability and resilience.
result Different cryptocurrencies experienced shifts in their network roles during the FTX crisis.

We provide investment advice for an individual who wishes to minimize her lifetime poverty, with a penalty for bankruptcy or ruin. We measure poverty via a non-negative, non-increasing function of (running) wealth. Thus, the lower wealth falls and the longer wealth stays low, the greater the penalty. This paper general…

2015-09-05abs ↗pdf ↗

We present a simple model of firm rating evolution. We consider two sources of defaults: individual dynamics of economic development and Potts-like interactions between firms. We show that such a defined model leads to phase transition, which results in collective defaults. The existence of the collective phase depends…

2009-04-28abs ↗pdf ↗

Corporate insolvency can have a devastating effect on the economy. With an increasing number of companies making expansion overseas to capitalize on foreign resources, a multinational corporate bankruptcy can disrupt the world's financial ecosystem. Corporations do not fail instantaneously; objective measures and rigor…

2018-02-14abs ↗pdf ↗

Study defines and optimizes bank reliability using LR and PSO.

problem Lack of reliability concept in financial services.
method Logistic Regression (LR) for initial estimation, Particle Swarm Optimization (PSO) for optimization.
result Optimal financial ratios maximize bank reliability.

Share prices of financial companies from the S&P 500 list have been modeled by a linear function of consumer price indices in the USA. The Johansen and Engle-Granger tests for cointegration both demonstrated the presence of an equilibrium long-term relation between observed and predicted time series. Econometrically, t…

2010-03-13abs ↗pdf ↗

We study an optimal dividend problem under a bankruptcy constraint. Firms face a trade-off between potential bankruptcy and extraction of profits. In contrast to previous works, general cash flow drifts, including Ornstein--Uhlenbeck and CIR processes, are considered. We provide rigorous proofs of continuity of the val…

2017-06-06abs ↗pdf ↗

In this paper, we introduce an insurance ruin model with adaptive premium rate, thereafter refered to as restructuring/refraction, in which classical ruin and bankruptcy are distinguished. In this model, the premium rate is increased as soon as the wealth process falls into the red zone and is brought back to its regul…

2013-06-19abs ↗pdf ↗

Our study shows that many firms would accumulate at zero output level (namely, Bankruptcy status) if a perfectly competitive market reaches full employment (namely, those people who should obtain employment have obtained employment). As a result, appearance of economic crisis is determined by two points; that is, (a). …

2010-10-22abs ↗pdf ↗

Academics and practitioners have studied over the years models for predicting firms bankruptcy, using statistical and machine-learning approaches. An earlier sign that a company has financial difficulties and may eventually bankrupt is going in \emph{default}, which, loosely speaking means that the company has been hav…

2020-02-17abs ↗pdf ↗