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.
The paper uses daily bond price data to estimate corporate default spreads, improving credit risk assessment.
The paper uses option theory to estimate corporate bond liquidity spreads.
Develops a three-currency HJM framework for Brazilian credit markets, finding significant credit spread differences between indexed segments.
This paper develops a two-dimensional structural framework for valuing credit default swaps and corporate bonds in the presence of default contagion. Modelling the values of related firms as correlated geometric Brownian motions with exponential default barriers, analytical formulae are obtained for both credit default…
Paper finds political networks reduce bond issuance costs in China.
Develops a new model to better predict corporate bond yields.
We explain a persistent cost-of-carry spread in EUA market and suggest ECB policy change.
Paper evaluates different models for predicting credit default swap volatility.
We give a detailed account of correlations between credit sector/quality and treasury curve factors, using the robust framework of the Barclays POINT Global Risk Model. Consistent with earlier studies, we find a strong negative correlation between sector spreads and rate shifts. However, we also observe that the correl…
Shorting IG ETFs can hedge bond portfolios during market drawdowns effectively.
CCR-CNN uses CNN to predict corporate credit ratings from financial data.
Large corporate credit models may be adapted for small business risk assessment.
Framework integrates financial and annual report data for better corporate credit ratings.
Private credit markets have expanded significantly, offering unique lending technology to private equity firms.
Study evaluates neural networks for corporate credit rating assessment.
We develop a generalization of the Black-Cox structural model of default risk. The extended model captures uncertainty related to firm's ability to avoid default even if company's liabilities momentarily exceeding its assets. Diffusion in a linear potential with the radiation boundary condition is used to mimic a compa…
The VIX is used to model corporate bond volatility and returns.
Model for corporate bond pricing with credit rating migration, solving a double free boundary problem.
The term structure of credit spreads is studied with an aim to predict its future movements. A completely new approach to tackle this problem is presented, which utilizes nonlinear parametric models. The Brain-Cousens regression model with five parameters is chosen to describe the term structure of credit spreads. Furt…
New model predicts credit spreads using stochastic CIR++ intensities.
This paper uses RL to optimize bid-ask spreads for illiquid corporate bonds.
Conditions of Stability for explicit finite difference scheme and some results of numerical analysis for a unified 2 factor model of structural and reduced form types for corporate bonds with fixed discrete coupon are provided. It seems to be difficult to get solution formula for PDE model which generalizes Agliardi's …
Model estimates LIBOR rates and finds COVID-19 spread spike due to credit risk.
AI improves credit rating predictions over traditional methods.
We propose an option approach for pricing bond illiquidity that is reminiscent of the celebrated work of Longstaff (1995) on the non-marketability of some non-dividend-paying shares in IPOs. This approach describes a quite common situation in the fixed income market: it is rather usual to find issuers that, besides liq…
We compare observed corporate cumulative default probabilities to those calculated using a stochastic model based on an extension of the work of Black and Cox and find that corporations default as if via diffusive dynamics. The model, based on a contingent-claims analysis of corporate capital structure, is easily calib…
According to theoretical models of valuing risky corporate securities, risk of default is primary component in overall yield spread. However, sizable empirical literature considers it otherwise by giving more importance to non-default risk factors. Current study empirically attempts to provide relative solution to this…
Extracts credit-relevant information from earnings calls.
This study compares neural networks, SVM, and decision trees for corporate credit rating predictions.
We provide analytical pricing formula of corporate defaultable bond with both expected and unexpected default in the case with stochastic default intensity. In the case with constant short rate and exogenous default recovery using PDE method, we gave some pricing formula of the defaultable bond under the conditions tha…
New method estimates corporate default probabilities using indirect data.
AXI assesses bank funding costs transparently, improving loan pricing and reducing financial risk.
Traditional methods outperform LLMs in forecasting corporate credit ratings.
Proposes a sparsity algorithm to improve corporate credit ratings.
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 improves bond market making by adjusting hit-ratios for client flow quality.
We develop an efficient method to calibrate CDS spreads using asymptotic approximations.
New model prices corporate bonds by accounting for non-hedgeable risk.
The paper explains how to construct a credit spread curve from bond prices.
We show that stochastic recovery always leads to counter-intuitive behaviors in the risk measures of a CDO tranche - namely, continuity on default and positive credit spread risk cannot be ensured simultaneously. We then propose a simple recovery variance regularization method to control the magnitude of negative credi…
In this paper, we propose a methodology based on piece-wise homogeneous Markov chain for credit ratings and a multivariate model of the credit spreads to evaluate the financial risk in European Union (EU). Two main aspects are considered: how the financial risk is distributed among the European countries and how large …
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…
Corporate defaults may be triggered by some major market news or events such as financial crises or collapses of major banks or financial institutions. With a view to develop a more realistic model for credit risk analysis, we introduce a new type of reduced-form intensity-based model that can incorporate the impacts o…
Companies do not operate in a vacuum. As companies move towards an increasingly specialized production function and their reach is becoming truly global, their aptitude in managing and shaping their inter-organizational network is a determining factor in measuring their health. Current models of company financial healt…
This study uses TDA to map corporate failure, revealing distinct regions of risk.
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…
This paper studies the valuation of a class of default swaps with the embedded option to switch to a different premium and notional principal anytime prior to a credit event. These are early exercisable contracts that give the protection buyer or seller the right to step-up, step-down, or cancel the swap position. The …
We compare two models of corporate default by calculating the Jeffreys-Kullback-Leibler divergence between their predicted default probabilities when asset correlations are either high or low. Our main results show that the divergence between the two models increases in highly correlated, volatile, and large markets, b…