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The largest US banks are required by regulatory mandate to estimate the operational risk capital they must hold using an Advanced Measurement Approach (AMA) as defined by the Basel II/III Accords. Most use the Loss Distribution Approach…

Risk Management · Quantitative Finance 2014-12-01 J. D. Opdyke

In Bayesian inference, an unknown measurement uncertainty is often quantified in terms of a Gamma distributed precision parameter, which is impractical when prior information on the standard deviation of the measurement uncertainty shall be…

Methodology · Statistics 2021-01-19 Manuel M. Eichenlaub

We study two Bayesian (Reference Intrinsic and Jeffreys prior) and two frequentist (MLE and PWM) approaches to calibrating the Pareto and related distributions. Three of these approaches are compared in a simulation study and all four to…

Methodology · Statistics 2019-11-25 James Sharpe , Miguel A Juarez

Under the Basel II standards, the Operational Risk (OpRisk) advanced measurement approach allows a provision for reduction of capital as a result of insurance mitigation of up to 20%. This paper studies the behaviour of different insurance…

Risk Management · Quantitative Finance 2010-11-04 Gareth W. Peters , Aaron D. Byrnes , Pavel V. Shevchenko

Statistical models typically capture uncertainties in our knowledge of the corresponding real-world processes, however, it is less common for this uncertainty specification to capture uncertainty surrounding the values of the inputs to the…

Methodology · Statistics 2023-05-10 Samuel E. Jackson , David C. Woods

A new procedure is presented for the objective comparison and evaluation of default definitions. This allows the lender to find a default threshold at which the financial loss of a loan portfolio is minimised, in accordance with Basel II.…

Risk Management · Quantitative Finance 2021-03-01 Arno Botha , Conrad Beyers , Pieter de Villiers

In this paper we focus on the parameter estimation of dynamic load models with stochastic terms, in particular, load models where protection settings are uncertain, such as in aggregated air conditioning units. We show how the uncertainty…

Optimization and Control · Mathematics 2020-04-30 Daniel Adrian Maldonado , Vishwas Rao , Mihai Anitescu , Vivak Patel

Regulatory requirements dictate that financial institutions must calculate risk capital (funds that must be retained to cover future losses) at least annually. Procedures for doing this have been well-established for many years, but recent…

Computational Finance · Quantitative Finance 2017-05-22 Peter Mitic

Most of the banks' operational risk internal models are based on loss pooling in risk and business line categories. The parameters and outputs of operational risk models are sensitive to the pooling of the data and the choice of the risk…

Risk Management · Quantitative Finance 2015-05-12 Vivien Brunel

A new methodology for incorporating LGD correlation effects into the Basel II risk weight functions is introduced. This methodology is based on modelling of LGD and default event with a single loss variable. The resulting formulas for…

Other Condensed Matter · Physics 2008-12-02 Dirk Tasche

According to the Loss Distribution Approach, the operational risk of a bank is determined as 99.9% quantile of the respective loss distribution, covering unexpected severe events. The 99.9% quantile can be considered a tail event. As…

Risk Management · Quantitative Finance 2015-03-17 Nataliya Horbenko , Peter Ruckdeschel , Taehan Bae

Pricing extremely long-dated liabilities market consistently deals with the decline in liquidity of financial instruments on long maturities. The aim is to quantify the uncertainty of rates up to maturities of a century. We assume that the…

Computational Finance · Quantitative Finance 2013-12-19 Anne Balter , Antoon Pelsser , Peter Schotman

In this paper we consider the estimation of unknown parameters in Bayesian inverse problems. In most cases of practical interest, there are several barriers to performing such estimation, This includes a numerical approximation of a…

Methodology · Statistics 2025-02-07 Neil K. Chada , Ajay Jasra , Mohamed Maama , Raul Tempone

We propose a stochastic model allowing property and casualty insurers with multiple business lines to measure their liabilities for incurred claims risk and calculate associated capital requirements. Our model includes many desirable…

Risk Management · Quantitative Finance 2021-12-07 Carlos Andrés Araiza Iturria , Frédéric Godin , Mélina Mailhot

We present a Bayesian perspective on quantifying the uncertainty of graph signals estimated or reconstructed from imperfect observations. We show that many conventional methods of graph signal estimation, reconstruction and imputation, can…

Signal Processing · Electrical Eng. & Systems 2025-05-22 Lennard Rompelberg , Michael T. Schaub

The Solvency II Directive and Solvency Assessment and Management (the South African equivalent) give a Solvency Capital Requirement which is based on a 99.5% Value-at-Risk (VaR) calculation. This calculation involves aggregating individual…

Applications · Statistics 2018-04-06 Sean van der Merwe , Darren Steven , Martinette Pretorius

When undertaking cyber security risk assessments, we must assign numeric values to metrics to compute the final expected loss that represents the risk that an organization is exposed to due to cyber threats. Even if risk assessment is…

Computer Science and Game Theory · Computer Science 2017-12-19 Andrew Fielder , Sandra Konig , Emmanouil Panaousis , Stefan Schauer , Stefan Rass

The Basel II internal ratings-based (IRB) approach to capital adequacy for credit risk plays an important role in protecting the Australian banking sector against insolvency. We outline the mathematical foundations of regulatory capital for…

Risk Management · Quantitative Finance 2016-07-26 Marek Rutkowski , Silvio Tarca

Parameter estimation via unbinned maximum likelihood fits is central for many analyses performed in high energy physics. Unbinned maximum likelihood fits using event weights, for example to statistically subtract background contributions…

Data Analysis, Statistics and Probability · Physics 2022-05-09 Christoph Langenbruch

We address the common problem of calculating intervals in the presence of systematic uncertainties. We aim to investigate several approaches, but here describe just a Bayesian technique for setting upper limits. The particular example we…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Joel Heinrich , Craig Blocker , John Conway , Luc Demortier , Louis Lyons , Giovanni Punzi , Pekka K. Sinervo