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Risk management is an important practice in the banking industry. In this paper we develop a new methodology to estimate and predict the probability of default (PD) based on the rating transition matrices, which relates the rating…

Risk Management · Quantitative Finance 2018-03-28 Jinghai Shao , Siming Li , Yong Li

In the paper, we study a new rate of convergence estimate for homogeneous discrete-time nonlinear Markov chains based on the Markov-Dobrushin condition. This result generalizes the convergence estimates for any positive number of transition…

Probability · Mathematics 2021-10-22 Aleksandr A. Shchegolev

We consider structural credit modeling in the important special case where the log-leverage ratio of the firm is a time-changed Brownian motion (TCBM) with the time-change taken to be an independent increasing process. Following the…

Statistical Finance · Quantitative Finance 2011-02-14 T. R. Hurd , Zhuowei Zhou

We analyze the fluctuation of the loss from default around its large portfolio limit in a class of reduced-form models of correlated firm-by-firm default timing. We prove a weak convergence result for the fluctuation process and use it for…

Probability · Mathematics 2015-02-20 Konstantinos Spiliopoulos , Justin A. Sirignano , Kay Giesecke

Supply chain disruptions constitute an often underestimated risk for financial stability. As in financial networks, systemic risks in production networks arises when the local failure of one firm impacts the production of others and might…

Statistical Finance · Quantitative Finance 2025-02-25 Jan Fialkowski , Christian Diem , András Borsos , Stefan Thurner

We show that Poisson regression, though often recommended over log-linear regression for modeling count and other non-negative variables in finance and economics, can be far from optimal when heteroskedasticity and sparsity -- two common…

Econometrics · Economics 2025-09-03 Agostino Capponi , Zhaonan Qu

This paper studies some temporal dependence properties and addresses the issue of parametric estimation for a class of state-dependent autoregressive models for nonlinear time series in which we assume a stochastic autoregressive…

Statistics Theory · Mathematics 2020-02-11 Fabio Gobbi , Sabrina Mulinacci

Time series subject to change in regime have attracted much interest in domains such as econometry, finance or meteorology. For discrete-valued regimes, some models such as the popular Hidden Markov Chain (HMC) describe time series whose…

Machine Learning · Computer Science 2021-02-26 Fatoumata Dama , Christine Sinoquet

We consider the setting where a collection of time series, modeled as random processes, evolve in a causal manner, and one is interested in learning the graph governing the relationships of these processes. A special case of wide interest…

Machine Learning · Computer Science 2016-08-30 Hossein Hosseini , Sreeram Kannan , Baosen Zhang , Radha Poovendran

This paper investigates the finite horizon risk-sensitive portfolio optimization in a regime-switching credit market with physical and information-induced default contagion. It is assumed that the underlying regime-switching process has…

Portfolio Management · Quantitative Finance 2021-07-28 Lijun Bo , Huafu Liao , Xiang Yu

We consider a risk-sensitive optimization of consumption-utility on infinite time horizon where the one-period investment gain depends on an underlying economic state whose evolution over time is assumed to be described by a discrete-time,…

Optimization and Control · Mathematics 2021-11-19 Anindya Goswami , Nimit Rana , Tak Kuen Siu

Survival analysis has become a standard approach for modelling time to default by time-varying covariates in credit risk. Unlike most existing methods that implicitly assume a stationary data-generating process, in practise, mortgage…

Machine Learning · Statistics 2026-01-29 Jianwei Peng , Stefan Lessmann

Relational data characterized by directed edges with count measurements are common in social science. Most existing methods either assume the count edges are derived from continuous random variables or model the edge dependency by…

Methodology · Statistics 2025-02-18 Wenqin Du , Bailey K. Fosdick , Wen Zhou

We propose a Markov chain model for credit rating changes. We do not use any distributional assumptions on the asset values of the rated companies but directly model the rating transitions process. The parameters of the model are estimated…

Risk Management · Quantitative Finance 2014-01-21 David Wozabal , Ronald Hochreiter

We study how the phenomenon of contagion can take place in the network of the world's stock exchanges due to the behavioral trait "blindeness to small changes". On large scale individual, the delay in the collective response may…

General Finance · Quantitative Finance 2016-02-25 Lucia Bellenzier , Jørgen Vitting Andersen , Giulia Rotundo

We propose a new Bayesian Markov switching regression model for multidimensional arrays (tensors) of binary time series. We assume a zero-inflated logit regression with time-varying parameters and apply it to multilayer temporal networks.…

Methodology · Statistics 2019-07-05 Monica Billio , Roberto Casarin , Matteo Iacopini

This paper develops a structural credit risk model to characterize the difference between the economic and recorded default times for a firm. Recorded default occurs when default is recorded in the legal system. The economic default time is…

Risk Management · Quantitative Finance 2015-03-17 Xin Guo , Robert A Jarrow , Adrien de Larrard

In recent years research on credit risk modelling has mainly focused on default probabilities. Recovery rates are usually modelled independently, quite often they are even assumed constant. Then, however, the structural connection between…

Risk Management · Quantitative Finance 2015-03-06 Alexander F. R. Koivusalo , Rudi Schäfer

Multiple systems estimation using a Poisson loglinear model is a standard approach to quantifying hidden populations where data sources are based on lists of known cases. Information criteria are often used for selecting between the large…

Methodology · Statistics 2023-11-23 Bernard W. Silverman , Lax Chan , Kyle Vincent

We study systemic default contagion in sparse financial networks and develop a framework for deciding when aggregate exposure matrices are reliable and when node-level network information changes tail risk and control design. The first…

Optimization and Control · Mathematics 2026-05-26 Aoxin Zhang , Yingzhe Wang