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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.

169,181 papers · 148 categories

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85169254338 · Jun 202019922001200920182026
48 results for credit system

Complex network theory models China's credit system to control systemic risk.

problem Insufficient understanding of China's credit network structure during financial crises.
method Constructed bipartite financial institution-firm network and analyzed its typological properties.
result Credit network structure can amplify local risks to the whole economy.

Study uses geometric algebra to analyze credit cycles, revealing dangerous feedback loops.

problem Understanding and predicting dangerous feedback loops in credit cycles.
method Represent economic states as multi-vectors in Clifford algebra, focusing on bivector elements for rotational coupling.
result Geometric relationship between unemployment and credit contraction shifts from simple correlation to dangerous rotational dynamics during crises.

Unified framework models credit cycles and systemic risk.

problem Inadequate classical models for bubbles, crises, and credit cycles.
method Marshall-Walras price formation process and mathematical formalism.
result Unified framework reflects different economic states and systemic risk.

Paper develops a credit scoring system for micro-loans, addressing interpretability and data quality challenges.

problem Developing a credit scoring system for micro-loans with interpretability and data quality concerns.
method Introduces semi-supervised algorithm to aid model development and evaluates its performance.
result Semi-supervised algorithm aids in model development and demonstrates improved performance.

With negative growth in real production in many countries and debt levels which become an increasing burden on developed societies, the calls for a change in economic policy and even the monetary system become louder and increasingly impatient. We research the consequences of a system of credit and debt, that still all…

2011-11-13abs ↗pdf ↗

Investment strategy optimized for markets and credit risks.

problem Optimal investment/consumption problem in models with market and credit risk dependencies.
method Martingale approach and analysis of nonlinear Hamilton-Jacobi-Bellman equations transformed into semi-linear PDEs.
result Explicit representations for optimal strategy, consumption path, and wealth process.

System designs for analyzing and pricing non-performing consumer credit portfolios.

problem Technical challenges in analyzing and pricing portfolios of non-performing consumer credit loans.
method Bottom-up architecture, simultaneous quantile regression, R-copula, Gaussian one-factor copula model.
result Successfully developed a methodology for analyzing credit portfolio risks of consumer loans.

Using particle system methodologies we study the propagation of financial distress in a network of firms facing credit risk. We investigate the phenomenon of a credit crisis and quantify the losses that a bank may suffer in a large credit portfolio. Applying a large deviation principle we compute the limiting distribut…

2007-04-11abs ↗pdf ↗

Expert system predicts credit card charge-offs using macroeconomic indicators.

problem Managing charge-off rates in the credit card industry.
method Developed an expert system using machine learning and macroeconomic indicators.
result Achieved mean squared error values of 1.15E-03 and 1.04E-03.

Modeling financial institution dependence structures for systemic risk.

problem Understanding and measuring systemic risk in financial systems.
method Dynamic model of dependence structure using Markov structures of joint credit migrations.
result Different Markov structures with distinct dependence structures lead to varying systemic instability.

The importance of adequately modeling credit risk has once again been highlighted in the recent financial crisis. Defaults tend to cluster around times of economic stress due to poor macro-economic conditions, {\em but also} by directly triggering each other through contagion. Although credit default swaps have radical…

2012-02-14abs ↗pdf ↗

Private credit markets have expanded significantly, offering unique lending technology to private equity firms.

problem Understanding the growth and characteristics of private credit markets.
method Systematic survey of academic literature, development of integrated theoretical framework, empirical evidence.
result Private credit markets offer a distinct lending technology with higher spreads over syndicated loans.

Study dynamic hedging of credit risk using a new model.

problem Dynamic hedging of counterparty risk for credit derivatives.
method Empirically driven credit model with interacting default intensities; Galtchouk-Kunita-Watanabe decomposition; closed-form risk minimizing strategy.
result Closed-form representation for risk minimizing strategy in nonlinear recursive systems.

Paper proposes a framework for precise daily default risk prediction of Chinese credit bonds.

problem Inadequate and inaccurate bond information disclosure creates risk of default for investors.
method Framework includes summarizing factors impacting defaults, constructing a risk index system, and using ConvLSTM neural network for prediction.
result The model provides more responsive and accurate daily default risk predictions than authoritative ratings.

MRC improves credit assignment in multi-agent LLM systems, achieving high returns and transparency.

problem Lack of principled credit assignment in multi-agent LLM decision systems, vulnerability to regime shifts, and limited transparency.
method Market Regime Council (MRC) computes exact Shapley credits, uses exponentially weighted performance histories, Bayesian adaptive mixture, and regime-dependent multipliers.
result MRC achieves a Sharpe ratio of 1.51 and a cumulative return of 440.1% over 1,037 trading days, ranking first on CR, SR, and IR.

This paper develops the Jungle model in a credit portfolio framework. The Jungle model is able to model credit contagion, produce doubly-peaked probability distributions for the total default loss and endogenously generate quasi phase transitions, potentially leading to systemic credit events which happen unexpectedly …

2015-02-17abs ↗pdf ↗

The study develops a machine learning system for credit scoring and default prediction.

problem Developing a robust credit rating and default prediction system.
method Combines NLP, AE, GBM, DE, and SHAP/LIME for model interpretability.
result Obtained excellent out-of-sample performance in credit rating and default prediction.

This work explores the characteristics of financial contagion in networks whose links distributions approaches a power law, using a model that defines banks balance sheets from information of network connectivity. By varying the parameters for the creation of the network, several interbank networks are built, in which …

2014-10-09abs ↗pdf ↗

The stability of the financial system is associated with systemic risk factors such as the concurrent default of numerous small obligors. Hence it is of utmost importance to study the mutual dependence of losses for different creditors in the case of large, overlapping credit portfolios. We analytically calculate the m…

2017-06-29abs ↗pdf ↗

The paper introduces a health-informed policy gradient method for multi-agent reinforcement learning.

problem Optimizing joint reward functions in multi-agent systems with varying agent health.
method Health-informed credit assignment in a multi-agent proximal policy optimization algorithm.
result Significant improvement in learning performance compared to traditional methods.

This paper addresses credit valuation adjustment with a new closeout convention.

problem Accurate estimation of financial claim value considering counterparty credit risk.
method Theoretical and computational analysis of a nonlinear valuation system using neural networks.
result A neural network-based algorithm effectively solves the high-dimensional nonlinear valuation system.

Optimal credit and consumption strategies in a switching market with default contagion.

problem Optimal portfolio and consumption decisions in a credit market with default contagion.
method Cobb-Douglas utility, recursive ODE system, backward solution from all-default state.
result Existence and uniqueness of optimal feedback controls, verification theorem.

Credit networks represent a way of modeling trust between entities in a network. Nodes in the network print their own currency and trust each other for a certain amount of each other's currency. This allows the network to serve as a decentralized payment infrastructure---arbitrary payments can be routed through the net…

2010-07-03abs ↗pdf ↗

DeRisk improves credit risk prediction using deep learning.

problem Challenges in training deep neural networks with real-world financial data.
method DeRisk, an effective deep learning framework for credit risk prediction.
result DeRisk outperforms statistical learning methods in credit risk prediction.

Paper proposes an intelligent credit limit management system using causal inference.

problem Traditional credit limit management strategies are heuristic and not data-driven.
method Conditional independence testing, response model, log transformation, GBDT encoding, non-linear transformation on features, well-designed metric.
result The proposed approach effectively manages credit limits and incorporates diminishing marginal effects.

We set up a structural model to study credit risk for a portfolio containing several or many credit contracts. The model is based on a jump--diffusion process for the risk factors, i.e. for the company assets. We also include correlations between the companies. We discuss that models of this type have much in common wi…

2007-07-24abs ↗pdf ↗

The proposed model is aimed to reveal important patterns in the behavior of a simplified financial system. The patterns could be detected as regular cycles consisting of debt bubbles and crises. Financial cycles have a well defined structure and form periodic sequences along the axis of credit expansion while retaining…

2016-07-05abs ↗pdf ↗

Inspired by the bankruptcy of Lehman Brothers and its consequences on the global financial system, we develop a simple model in which the Lehman default event is quantified as having an almost immediate effect in worsening the credit worthiness of all financial institutions in the economic network. In our stylized desc…

2010-02-04abs ↗pdf ↗

Bayesian Neural Networks improve credit card default prediction and provide feature importance.

problem Lack of interpretability and uncertainty measures in neural network models for credit risk.
method Developed and compared BNNs trained by Gaussian approximation and Hybrid Monte Carlo.
result BNNs with Automatic Relevance Determination outperform normal BNNs in credit card default prediction.

We introduce a dynamic credit portfolio framework where optimal investment strategies are robust against misspecifications of the reference credit model. The risk-averse investor models his fear of credit risk misspecification by considering a set of plausible alternatives whose expected log likelihood ratios are penal…

2016-03-27abs ↗pdf ↗

We build a statistical ensemble representation of two economic models describing respectively, in simplified terms, a payment system and a credit market. To this purpose we adopt the Boltzmann-Gibbs distribution where the role of the Hamiltonian is taken by the total money supply (i.e. including money created from debt…

2011-09-02abs ↗pdf ↗

Paper introduces Cycles Protocol to integrate trade credit into market clearing.

problem Liquidity embedded in trade credit outside formal settlement infrastructures.
method Distributed, multilateral clearing mechanism based on double-entry accounting.
result Cycles Protocol maximizes balance sheet compression without redistributing counterparty risk.