arXiv · arXiv q-fin · 2018
A justification of the Basel liquidity formula for risk capital in the trading book is given under the assumption that market risk-factor changes form a Gaussian white noise process over 10-day time steps and changes to P&L are linear in the risk-factor changes. A generalization of the formula is derived under the more general assumption that risk-factor changes are multivariate elliptical. It is shown that the Basel…
Janine Balter, Alexander J. McNeil
arXiv · arXiv q-fin · 2011
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 modeling, Gap Risk, Re-hypothecation, Wrong Way Risk, Basel III, inclusion of Funding costs, First t…
Damiano Brigo
arXiv · arXiv q-fin · 2025
Risk allocation, the decomposition of a portfolio-wide risk measure into component contributions, is a fundamental problem in financial risk management due to the non-additive nature of risk measures, the layered organizational structures of financial institutions, and the range of possible allocation strategies characterized by different rationales and properties. In this work, we conduct a systematic review of the …
Marco Scaringi, Marco Bianchetti
arXiv · arXiv q-fin · 2023
Inspired by the recent debate on the macroeconomic implications of the new bank regulatory standards known as Basel III, we tried to find out in this study that the impact of Basel III liquidity and capital requirements in Bangladesh proposed by Basel Committee on Banking Supervision (BCBS, 2010a). A small set of macro variables, using a sample of 22 private commercial banks operating in Bangladesh for the period of …
Dipti Rani Hazra, Md. Shah Naoaj, Mohammed Mahinur Alam, Abdul Kader
arXiv · arXiv q-fin · 2014
The Basel II internal ratings-based (IRB) approach to capital adequacy for credit risk implements an asymptotic single risk factor (ASRF) model. Measurements from the ASRF model of the prevailing state of Australia's economy and the level of capitalisation of its banking sector find general agreement with macroeconomic indicators, financial statistics and external credit ratings. However, given the range of economic …
Silvio Tarca, Marek Rutkowski
arXiv · arXiv q-fin · 2013
Financial institutions are currently required to meet more stringent capital requirements than they were before the recent financial crisis; in particular, the capital requirement for a large bank's trading book under the Basel 2.5 Accord more than doubles that under the Basel II Accord. The significant increase in capital requirements renders it necessary for banks to take into account the constraint of capital requ…
Zaiwen Wen, Xianhua Peng, Xin Liu, Xiaoling Sun, Xiaodi Bai
arXiv · arXiv q-fin · 2013
The management of operational risk in the banking industry has undergone significant changes over the last decade due to substantial changes in operational risk environment. Globalization, deregulation, the use of complex financial products and changes in information technology have resulted in exposure to new risks very different from market and credit risks. In response, Basel Committee for banking Supervision has …
Pavel V. Shevchenko, Gareth W. Peters
arXiv · arXiv q-fin · 2026
We develop a continuous-time structural dynamic model to determine the exact insolvency regions of banks arising from the non-linear interaction between liquidity and credit risk. While existing literature predominantly treats these risks in isolation or via reduced-form specifications, we explicitly model the feedback loop where funding shocks and regulatory constraints force balance-sheet adjustments that can lead …
Nader Karimi, Davood Ahmadian
arXiv · arXiv q-fin · 2024
Credit Scoring is one of the problems banks and financial institutions have to solve on a daily basis. If the state-of-the-art research in Machine and Deep Learning for finance has reached interesting results about Credit Scoring models, usage of such models in a heavily regulated context such as the one in banks has never been done so far. Our work is thus a tentative to challenge the current regulatory status-quo a…
Abdollah Rida
arXiv · arXiv q-fin · 2022
Despite the amount of savings available and the money supply managed by financial institutions, significant market failures and the failure of carbon pricing strategies prevent sufficient financing of the transition, notably through bank credit. Aware of the links between natural, monetary and productive aggregates, we propose the development of ''eco-systemic'' prudential policies by exposing the interdependence bet…
Laura Chémali, Camille Souffron
arXiv · arXiv q-fin · 2017
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 have gained in importance with the newly adopted IFRS 9 accounting standard. Here, the multi-year PDs can be used to calculate the so-called expected credit losses (ECL) over the ent…
Volodymyr Perederiy
arXiv · arXiv q-fin · 2015
During recent years the counterparty risk subject has received a growing attention because of the so called Basel Accord. In particular the Basel III Accord asks the banks to fulfill finer conditions concerning counterparty credit exposures arising from banks' derivatives, securities financing transactions, default and downgrade risks characterizing the Over The Counter (OTC) derivatives market, etc. Consequently the…
M. Bonollo, L. Di Persio, I. Oliva, A. Semmoloni
arXiv · arXiv q-fin · 2014
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 credit risk, and extend the model specification of the IRB approach to a more general setting than the usual Gaussian case. It rests on the proposition that quantiles of the distr…
Marek Rutkowski, Silvio Tarca
arXiv · arXiv q-fin · 2013
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 nominal total credit used by non-financial corporations. Such frequent and intense fluctuations are f…
Stefano Olgiati, Alessandro Danovi
arXiv · arXiv q-fin · 2009
This paper proposes a new methodology to compute Value at Risk (VaR) for quantifying losses in credit portfolios. We approximate the cumulative distribution of the loss function by a finite combination of Haar wavelets basis functions and calculate the coefficients of the approximation by inverting its Laplace transform. In fact, we demonstrate that only a few coefficients of the approximation are needed, so VaR can …
Josep J. Masdemont, Luis Ortiz-Gracia
arXiv · arXiv · 2026
Agent skills, structured packages of procedural knowledge and executable resources that agents dynamically load at inference time, have become a reliable mechanism for augmenting LLM agents. Yet inference-time skill augmentation is fundamentally limited: retrieval noise introduces irrelevant guidance, injected skill content imposes substantial token overhead, and the model never truly acquires the knowledge it merely…
Zhengxi Lu, Zhiyuan Yao, Jinyang Wu, Chengcheng Han, Qi Gu
arXiv · arXiv · 2026
Multimodal time-to-event prediction often requires integrating sensitive data distributed across multiple parties, making centralized model training impractical due to privacy constraints. At the same time, most existing multimodal survival models produce single deterministic predictions without indicating how confident the model is in its estimates, which can limit their reliability in real-world decision making. To…
Abhilash Kar, Basisth Saha, Tanmay Sen, Biswabrata Pradhan
arXiv · arXiv · 2026
Generating synthetic financial time series that preserve the statistical properties of real market data is essential for stress testing, risk model validation, and scenario design. Existing approaches struggle to simultaneously reproduce heavy-tailed distributions, negligible linear autocorrelation, and persistent volatility clustering. We developed a hybrid hidden Markov framework that discretized excess growth rate…
Abdulrahman Alswaidan, Jeffrey D. Varner