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.
AI enhances bank credit risk management through deep learning and data analysis.
Model analyzes systemic risk in banking systems using stochastic differential equations.
Analysis finds no evidence of banks managing deposit run risk prior to 2023 Regional Banking Crisis.
Framework simulates systemic risk in South African banking sector.
In [1] Zawadoski introduces a banking network model in which the asset and counter-party risks are treated separately and the banks hedge their assets risks by appropriate OTC contracts. In his model, each bank has only two counter-party neighbors, a bank fails due to the counter-party risk only if at least one of its …
Modeling banking system dynamics to govern systemic risk.
Study models systemic risks in BRICS banks under geopolitical shocks.
Derivatives impact U.S. banking sector's systemic risk, but loan and leverage ratios are more significant.
Study uses neural networks to predict credit risk in banks.
Systemic risk in banking systems remains a crucial issue that it has not been completely understood. In our toy model, banks are exposed to two sources of risks, namely, market risk from their investments in assets external to the banking system and credit risk from their lending in the interbank market. By and large, …
Complex non-linear interactions between banks and assets we model by two time-dependent Erdős Renyi network models where each node, representing bank, can invest either to a single asset (model I) or multiple assets (model II). We use dynamical network approach to evaluate the collective financial failure---systemic ri…
CERM calculates climate risks in bank loans.
The paper models systemic risk in European and U.S. banks using factor copulas.
As economic entities become increasingly interconnected, a shock in a financial network can provoke significant cascading failures throughout the system. To study the systemic risk of financial systems, we create a bi-partite banking network model composed of banks and bank assets and propose a cascading failure model …
Study identifies key firms contributing to systemic risk in Austrian financial network.
Study examines large banks' role in interbank markets using game theory.
The banking systems that deal with risk management depend on underlying risk measures. Following the Basel II accord, there are two separate methods by which banks may determine their capital requirement. The Value at Risk measure plays an important role in computing the capital for both approaches. In this paper we an…
Modeling bank leverage dynamics to understand systemic risk in financial markets.
Model shows how banks' hidden-to-maturity accounting can mask run risk and lead to financial instability.
This study uses high-frequency data to identify early warning signals for bank crises.
LIBOR-linked borrowing exposes venture banks to systemic risk without improving profitability.
The study examines how limited liability and haircut affect a bank's loan portfolio's liquidity risk.
It had been believed in the conventional practice that the risk of a bank going bankrupt is lessened in a straightforward manner by transferring the risk of loan defaults. But the failure of American International Group in 2008 posed a more complex aspect of financial contagion. This study presents an extension of the …
The question of how to stabilize financial systems has attracted considerable attention since the global financial crisis of 2007-2009. Recently, Beale et al. ("Individual versus systemic risk and the regulator's dilemma", Proc Natl Acad Sci USA 108: 12647-12652, 2011) demonstrated that higher portfolio diversity among…
The negative externalities from an individual bank failure to the whole system can be huge. One of the key purposes of bank regulation is to internalize the social costs of potential bank failures via capital charges. This study proposes a method to evaluate and allocate the systemic risk to different countries/regions…
On March 4th 2016 the Basel Committee on Banking Supervision published a consultative document where a new methodology, called the Standardized Measurement Approach (SMA), is introduced for computing Operational Risk regulatory capital for banks. In this note, the behavior of the SMA is studied under a variety of hypot…
Geospatial framework assesses climate risks for California's banking and exposed sectors.
New systemic risk models for banks choosing their group memberships.
The interconnectedness of financial institutions affects instability and credit crises. To quantify systemic risk we introduce here the PD model, a dynamic model that combines credit risk techniques with a contagion mechanism on the network of exposures among banks. A potential loss distribution is obtained through a m…
Regulation and risk management in banks depend on underlying risk measures. In general this is the only purpose that is seen for risk measures. In this paper we suggest that the reporting of risk measures can be used to determine the loss distribution function for a financial entity. We demonstrate that a lack of suffi…
Paper revisits HVA to address model risk in banking.
Paper studies central bank's strategy to control systemic risk in interbank system.
Model predicts Mozambique bank failures, aiding risk management.
Survey examines types of systemic risk in financial networks.
We develop the first basic Operational Risk perspective on key risk management issues associated with the development of new forms of electronic currency in the real economy. In particular, we focus on understanding the development of new risks types and the evolution of current risk types as new components of financia…
We propose a new methodology based on the Marshall-Olkin (MO) copula to model cross-border systemic risk. The proposed framework estimates the impact of the systematic and idiosyncratic components on systemic risk. Initially, we propose a maximum-likelihood method to estimate the parameter of the MO copula. In order to…
Diversification increases systemic risk, contrary to belief.
This paper analyzes how banking risks spread through sentiment and policy shocks.
We propose a simple model of inter-bank borrowing and lending where the evolution of the log-monetary reserves of banks is described by a system of diffusion processes coupled through their drifts in such a way that stability of the system depends on the rate of inter-bank borrowing and lending. Systemic risk is ch…
Modeling central bank strategy to minimize risk in pegged currency markets.
On June 26th, 2004, Central bank governors and the heads of bank supervisory authorities in the Group of Ten (G10) countries issued a press release and endorsed the publication of "International Convergence of Capital Measurement and Capital Standards: a Revised Framework", the new capital adequacy framework commonly k…
Modeling banking contagion using epidemiological methods.
This study presents an ANWSER model (asset network systemic risk model) to quantify the risk of financial contagion which manifests itself in a financial crisis. The transmission of financial distress is governed by a heterogeneous bank credit network and an investment portfolio of banks. Bankruptcy reproductive ratio …
Study examines credit risk's impact on Vietnamese banks' financial performance.
This paper investigates two mechanisms of financial contagion that are, firstly, the correlated exposure of banks to the same source of risk, and secondly the direct exposure of banks in the interbank market. It will consider a random network of banks which are connected through the inter-bank market and will discuss t…
Banks in the interbank network can not assess the true risks associated with lending to other banks in the network, unless they have full information on the riskiness of all the other banks. These risks can be estimated by using network metrics (for example DebtRank) of the interbank liability network which is availabl…
Develops a framework to assess systemic risk in the economy using bank-firm network data.
New method approximates systemic risk using node properties, revealing network structures that amplify risk.