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.
This paper improves credit line impact analysis by considering spending as a distribution.
An analysis of the Japanese credit market in 2004 between banks and quoted firms is done in this paper using the tools of the networks theory. It can be pointed out that: (i) a backbone of the credit channel emerges, where some links play a crucial role; (ii) big banks privilege long-term contracts; the "minimal spanni…
In this paper we formulate a corporate bond (CB) pricing model for deriving the term structure of default probabilities (TSDP) and the recovery rate (RR) for each pair of industry factor and credit rating grade, and these derived TSDP and RR are regarded as what investors imply in forming CB prices in the market at eac…
We prove that the default times (or any of their minima) in the dynamic Gaussian copula model of Cr{é}pey, Jeanblanc, and Wu (2013) are invariance times in the sense of Cr{é}pey and Song (2017), with related invariance probability measures different from the pricing measure. This reflects a departure from the immersion…
One of the key elements in the banking industry rely on the appropriate selection of customers. In order to manage credit risk, banks dedicate special efforts in order to classify customers according to their risk. The usual decision making process consists in gathering personal and financial information about the borr…
AXI assesses bank funding costs transparently, improving loan pricing and reducing financial risk.
Improved credit scoring model with explainability.
PerfGD solves model-induced data shifts by finding optimal points.
The paper proposes a method to detect credit card fraud using sparse Gaussian approximations.
The paper introduces new processors for fair credit scoring.
This paper is a contribution to the Proceedings of the Workshop Complexity, Metastability and Nonextensivity held in Erice 20-26 July 2004, to be published by World Scientific. We propose a generalization to Merton's model for evaluating credit spreads. In his original work, a company's assets were assumed to follow a …
Enhances credit card limit adjustments by considering treatment uncertainty and prediction criteria.
This paper examines the dividend and investment policies of a cash constrained firm that has access to costly external funding. We depart from the literature by allowing the firm to issue collateralized debt to increase its investment in productive assets resulting in a performance sensitive interest rate on debt. We f…
We present a study of price impact in the over-the-counter credit index market, where no limit order book is used. Contracts are traded via dealers, that compete for the orders of clients. Despite this distinct microstructure, we successfully apply the propagator technique to estimate the price impact of individual tra…
Study shows how to better estimate credit provisions and economic capital.
Study shows how macroprudential policies affect credit growth in Israel, especially in housing and business sectors.
Unified view on selective credit assignment for reinforcement learning.
We consider the task of mapping pseudocode to long programs that are functionally correct. Given test cases as a mechanism to validate programs, we search over the space of possible translations of the pseudocode to find a program that passes the validation. However, without proper credit assignment to localize the sou…
We apply Geometric Arbitrage Theory to obtain results in mathematical finance for credit markets, which do not need stochastic differential geometry in their formulation. We obtain closed form equations involving default intensities and loss given defaults characterizing the no-free-lunch-with-vanishing-risk condition …
This paper develops a machine learning model to assess credit risk in UAE commercial banks.
The existence of asymmetric information has always been a major concern for financial institutions. Financial intermediaries such as commercial banks need to study the quality of potential borrowers in order to make their decision on corporate loans. Classical methods model the default probability by financial ratios u…
Study evaluates SHAP for credit card default model consistency.
Large corporate credit models may be adapted for small business risk assessment.
Credit scores misclassify borrowers, especially minorities, leading to inequitable access.
Extracts credit-relevant information from earnings calls.
Bayesian and simulation methods predict credit default probabilities.
This paper studies the optimal dividend for a multi-line insurance group, in which each subsidiary runs a product line and is exposed to some external credit risk. The default contagion is considered such that one default event may increase the default probabilities of all surviving subsidiaries. The total dividend pro…
Paper simplifies default process modeling and credit valuation.
Study optimizes classifiers for credit card mail campaigns and default prediction.
CERM calculates climate risks in bank loans.
We consider the problem of constructing an appropriate multivariate model for the study of the counterparty credit risk in credit rating migration problem. For this financial problem different multivariate Markov chain models were proposed. However the markovian assumption may be inappropriate for the study of the dyna…
New insights into how to inspect and learn from multi-stage processes and AI reasoning.
Credit risk management in Italy is characterized, in the period June 2008 to June 2012, by frequent (frequency=0.5 cycles per year) and intense (peak amplitude: mean=39.2 billion Euros, s.e.=2.83 billion Euros) quarterly contractions and expansions around the mean (915.4 billion Euros, s.e.=3.59 billion Euros) of the n…
We present a dialogue on Counterparty Credit Risk touching on Credit Value at Risk (Credit VaR), Potential Future Exposure (PFE), Expected Exposure (EE), Expected Positive Exposure (EPE), Credit Valuation Adjustment (CVA), Debit Valuation Adjustment (DVA), DVA Hedging, Closeout conventions, Netting clauses, Collateral …
Method debiases alternative data for fair credit underwriting.
We propose a model for the credit markets in which the random default times of bonds are assumed to be given as functions of one or more independent "market factors". Market participants are assumed to have partial information about each of the market factors, represented by the values of a set of market factor informa…
We consider a structural credit model for a large portfolio of credit risky assets where the correlation is due to a market factor. By considering the large portfolio limit of this system we show the existence of a density process for the asset values. This density evolves according to a stochastic partial differential…
A new model uses a Levy-driven process to value credit index swaptions.
Model assesses credit risk using behavioral data from Experian and Bank of Italy.
This paper examines the possibility of using derivative-implied risk premia to explain stock returns. The rapid development of derivative markets has led to the possibility of trading various kinds of risks, such as credit and interest rate risk, separately from each other. This paper uses credit default swaps and equi…
The paper analyzes Lending Club's loan applicants to predict default risk.
CCR-CNN uses CNN to predict corporate credit ratings from financial data.
This paper builds a machine learning model to predict credit defaults for unsecured lending.
Derives metrics for DeFi vaults, addressing credit risk.
Study uses geometric algebra to analyze credit cycles, revealing dangerous feedback loops.
This paper uses PCA and FA for feature selection in credit rating.
BSAC improves credit scoring models by leveraging autoencoders and addressing imbalanced datasets.
New method to handle credit portfolio model uncertainties.