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Related papers: Phase transition in the Bayesian estimation of the…

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We discuss the parameter estimation of the probability of default (PD), the correlation between the obligors, and a phase transition. In our previous work, we studied the problem using the beta-binomial distribution. A non-equilibrium phase…

Risk Management · Quantitative Finance 2020-11-17 Masato Hisakado , Shintaro Mori

The estimation of probabilities of default (PDs) for low default portfolios by means of upper confidence bounds is a well established procedure in many financial institutions. However, there are often discussions within the institutions or…

Risk Management · Quantitative Finance 2013-09-04 Dirk Tasche

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

Banks and financial institutions all over the world manage portfolios containing tens of thousands of customers. Not all customers are high credit-worthy, and many possess varying degrees of risk to the Bank or financial institutions that…

Applications · Statistics 2021-09-17 Dominic Joseph

PD curve calibration refers to the transformation of a set of rating grade level probabilities of default (PDs) to another average PD level that is determined by a change of the underlying portfolio-wide PD. This paper presents a framework…

Risk Management · Quantitative Finance 2013-12-23 Dirk Tasche

The risk of a credit portfolio depends crucially on correlations between the probability of default (PD) in different economic sectors. Often, PD correlations have to be estimated from relatively short time series of default rates, and the…

Statistical Mechanics · Physics 2008-12-02 Bernd Rosenow , Rafael Weissbach , Frank Altrock

This paper proposes a simple technical approach for the analytical derivation of Point-in-Time PD (probability of default) forecasts, with minimal data requirements. The inputs required are the current and future Through-the-Cycle PDs of…

Risk Management · Quantitative Finance 2022-01-19 Volodymyr Perederiy

This paper proposes a hierarchical Bayesian model for probabilistic estimation of the electric vehicle battery capacity fade. Since the battery aging factors such as temperature, current, and state of charge are not fixed, and they change…

Systems and Control · Electrical Eng. & Systems 2019-11-05 Mehdi Jafari , Laura E. Brown , Lucia Gauchia

This work has the objective of estimating default probabilities and correlations of credit portfolios given default rate information through a Bayesian framework using Stan. We use Vasicek's single factor credit model to establish the…

Applications · Statistics 2024-01-23 Jesus A. Pinera-Esquivel

In banking practice, rating transition matrices have become the standard approach of deriving multi-year probabilities of default (PDs) from one-year PDs, the latter normally being available from Basel ratings. Rating transition matrices…

Risk Management · Quantitative Finance 2022-01-19 Volodymyr Perederiy

Banks are required to use long-term default probabilities (PDs) of their portfolios when calculating credit risk capital under internal ratings-based (IRB) models. However, the calibration models and historical data typically reflect…

Risk Management · Quantitative Finance 2025-08-22 Barbara Dömötör , Ferenc Illés

A possible data source for the estimation of asset correlations is default time series. This study investigates the systematic error that is made if the exposure pool underlying a default time series is assumed to be homogeneous when in…

Risk Management · Quantitative Finance 2019-09-12 Christoph Wunderer

Estimating time-varying correlation matrices is challenging because existing methods may adapt slowly to structural changes, impose insufficient regularization, or produce diffuse posterior uncertainty. In moderate dimensions, an additional…

Methodology · Statistics 2026-05-11 Daniel Andrew Coulson , David S. Matteson , Martin T. Wells

We introduce a voting model that is similar to a Keynesian beauty contest and analyze it from a mathematical point of view. There are two types of voters-copycat and independent-and two candidates. Our voting model is a binomial…

Data Analysis, Statistics and Probability · Physics 2015-05-13 Masato Hisakado , Shintaro Mori

The ongoing replication crisis in science has increased interest in the methodology of replication studies. We propose a novel Bayesian analysis approach using power priors: The likelihood of the original study's data is raised to the power…

Methodology · Statistics 2023-09-28 Samuel Pawel , Frederik Aust , Leonhard Held , Eric-Jan Wagenmakers

Meta-analysis is widely used to integrate results from multiple experiments to obtain generalized insights. Since meta-analysis datasets are often heteroscedastic due to varying subgroups and temporal heterogeneity arising from experiments…

Methodology · Statistics 2026-01-19 Kohsuke Kubota , Shonosuke Sugasawa , Keiichi Ochiai , Takahiro Hoshino

The power prior and its variations have been proven to be a useful class of informative priors in Bayesian inference due to their flexibility in incorporating the historical information by raising the likelihood of the historical data to a…

Methodology · Statistics 2022-04-14 Zifei Han , Keying Ye , Min Wang

The design of reliable indicators to anticipate critical transitions in complex systems is an im portant task in order to detect a coming sudden regime shift and to take action in order to either prevent it or mitigate its consequences. We…

Data Analysis, Statistics and Probability · Physics 2022-12-14 Martin Heßler , Oliver Kamps

Risk-averse investors often wish to exclude stocks from their portfolios that bear high credit risk, which is a measure of a firm's likelihood of bankruptcy. This risk is commonly estimated by constructing signals from quarterly accounting…

Computational Finance · Quantitative Finance 2025-03-06 Maksim Papenkov , Beau Robinette

We describe an efficient implementation of Bayesian quantum phase estimation in the presence of noise and multiple eigenstates. The main contribution of this work is the dynamic switching between different representations of the phase…

Quantum Physics · Physics 2021-06-09 Ewout van den Berg
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