arXiv - QuantFin - Risk Management最新文献_第5页

Global Balance and Systemic Risk in Financial Correlation Networks 金融关联网络中的全球平衡与系统性风险

arXiv - QuantFin - Risk Management Pub Date : 2024-07-19 DOI: arxiv-2407.14272

Paolo Bartesaghi, Fernando Diaz-Diaz, Rosanna Grassi, Pierpaolo Uberti

引用次数: 0

Autonomous Money Supply Strategy Utilizing Control Theory 利用控制论的自主货币供应战略

arXiv - QuantFin - Risk Management Pub Date : 2024-07-18 DOI: arxiv-2407.13232

Yuval Boneh

引用次数: 0

Bonus-malus Systems vs Delays in Claims Reporting and Settlement: Analysis of Ruin Probabilities 奖金制度与索赔报告和理赔延迟：毁约概率分析

arXiv - QuantFin - Risk Management Pub Date : 2024-07-17 DOI: arxiv-2408.00003

Dhiti Osatakul, Shuanming Li, Xueyuan Wu

引用次数: 0

Adaptive Money Market Interest Rate Strategy Utilizing Control Theory 利用控制论的自适应货币市场利率策略

arXiv - QuantFin - Risk Management Pub Date : 2024-07-15 DOI: arxiv-2407.10426

Yuval Boneh

{"title":"Adaptive Money Market Interest Rate Strategy Utilizing Control Theory","authors":"Yuval Boneh","doi":"arxiv-2407.10426","DOIUrl":"https://doi.org/arxiv-2407.10426","url":null,"abstract":"Decentralized Finance (DeFi) money markets have seen explosive growth in\u0000recent years, with billions of dollars borrowed in various cryptocurrency\u0000assets. Key to the safety of money markets is the implementation of interest\u0000rates that determine the cost of borrowing, and govern counterparty exposure\u0000and return. In traditional markets, interest rates are set by risk managers,\u0000portfolio managers, the Federal Reserve, and a myriad of other sources\u0000depending on the market function. DeFi enables an algorithmic approach that\u0000typically relies on interest rates being directly dependent on market\u0000utilization. The benefit of algorithmic interest rate management is the\u0000system's continual response to market behaviors in real time, and thus an\u0000inherent ability to mitigate risks on behalf of protocols and users. These\u0000interest rate strategies target an optimal utilization based on the protocol's\u0000risk threshold, but historically lack the ability to compensate for excessive\u0000or diminished utilization over time. This research investigates contemporary\u0000DeFi interest rate management strategies and their limitations. Furthermore,\u0000this paper introduces a time-weighted approach to interest rate management that\u0000implements a Proportional-Integral-Derivative (PID) control system to\u0000constantly adapt to market utilization patterns, addressing observed\u0000limitations.","PeriodicalId":501128,"journal":{"name":"arXiv - QuantFin - Risk Management","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141718016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A note on Skew Brownian Motion with two-valued drift and an application 关于具有两值漂移的斜布朗运动及其应用的说明

arXiv - QuantFin - Risk Management Pub Date : 2024-07-12 DOI: arxiv-2407.09321

Zaniar Ahmadi, Xiaowen Zhou

引用次数: 0

CAESar: Conditional Autoregressive Expected Shortfall CAESar：条件自回归预期缺口

arXiv - QuantFin - Risk Management Pub Date : 2024-07-09 DOI: arxiv-2407.06619

Federico Gatta, Fabrizio Lillo, Piero Mazzarisi

{"title":"CAESar: Conditional Autoregressive Expected Shortfall","authors":"Federico Gatta, Fabrizio Lillo, Piero Mazzarisi","doi":"arxiv-2407.06619","DOIUrl":"https://doi.org/arxiv-2407.06619","url":null,"abstract":"In financial risk management, Value at Risk (VaR) is widely used to estimate\u0000potential portfolio losses. VaR's limitation is its inability to account for\u0000the magnitude of losses beyond a certain threshold. Expected Shortfall (ES)\u0000addresses this by providing the conditional expectation of such exceedances,\u0000offering a more comprehensive measure of tail risk. Despite its benefits, ES is\u0000not elicitable on its own, complicating its direct estimation. However, joint\u0000elicitability with VaR allows for their combined estimation. Building on this,\u0000we propose a new methodology named Conditional Autoregressive Expected\u0000Shortfall (CAESar), inspired by the CAViaR model. CAESar handles dynamic\u0000patterns flexibly and includes heteroskedastic effects for both VaR and ES,\u0000with no distributional assumption on price returns. CAESar involves a\u0000three-step process: estimating VaR via CAViaR regression, formulating ES in an\u0000autoregressive manner, and jointly estimating VaR and ES while ensuring a\u0000monotonicity constraint to avoid crossing quantiles. By employing various\u0000backtesting procedures, we show the effectiveness of CAESar through extensive\u0000simulations and empirical testing on daily financial data. Our results\u0000demonstrate that CAESar outperforms existing regression methods in terms of\u0000forecasting performance, making it a robust tool for financial risk management.","PeriodicalId":501128,"journal":{"name":"arXiv - QuantFin - Risk Management","volume":"41 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141573134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The not-so-hidden risks of 'hidden-to-maturity' accounting: on depositor runs and bank resilience 隐性到期日 "会计的非隐性风险：关于存款人挤兑和银行复原力

arXiv - QuantFin - Risk Management Pub Date : 2024-07-03 DOI: arxiv-2407.03285

Zachary Feinstein, Grzegorz Halaj, Andreas Sojmark

{"title":"The not-so-hidden risks of 'hidden-to-maturity' accounting: on depositor runs and bank resilience","authors":"Zachary Feinstein, Grzegorz Halaj, Andreas Sojmark","doi":"arxiv-2407.03285","DOIUrl":"https://doi.org/arxiv-2407.03285","url":null,"abstract":"We build a balance sheet-based model to capture run risk, i.e., a reduced\u0000potential to raise capital from liquidity buffers under stress, driven by\u0000depositor scrutiny and further fueled by fire sales in response to withdrawals.\u0000The setup is inspired by the Silicon Valley Bank (SVB) meltdown in March 2023\u0000and our model may serve as a supervisory analysis tool to monitor build-up of\u0000balance sheet vulnerabilities. Specifically, we analyze which characteristics\u0000of the balance sheet are critical in order for banking system regulators to\u0000adequately assess run risk and resilience. By bringing a time series of SVB's\u0000balance sheet data to our model, we are able to demonstrate how changes in the\u0000funding and respective asset composition made SVB prone to run risk, as they\u0000were increasingly relying on held-to-maturity, aka hidden-to-maturity,\u0000accounting standards, masking revaluation losses in securities portfolios.\u0000Finally, we formulate a tractable optimisation problem to address the\u0000designation of held-to-maturity assets and quantify banks' ability to hold\u0000these assets without resorting to remarking. By calibrating this to SVB's\u0000balance sheet data, we shed light on the bank's funding risk and implied risk\u0000tolerance in the years 2020--22 leading up to its collapse.","PeriodicalId":501128,"journal":{"name":"arXiv - QuantFin - Risk Management","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141548172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Credit Risk Assessment Model for UAE Commercial Banks: A Machine Learning Approach 阿联酋商业银行信贷风险评估模型：机器学习方法

arXiv - QuantFin - Risk Management Pub Date : 2024-07-02 DOI: arxiv-2407.12044

Aditya Saxena, Dr Parizad Dungore

{"title":"Credit Risk Assessment Model for UAE Commercial Banks: A Machine Learning Approach","authors":"Aditya Saxena, Dr Parizad Dungore","doi":"arxiv-2407.12044","DOIUrl":"https://doi.org/arxiv-2407.12044","url":null,"abstract":"Credit ratings are becoming one of the primary references for financial\u0000institutions of the country to assess credit risk in order to accurately\u0000predict the likelihood of business failure of an individual or an enterprise.\u0000Financial institutions, therefore, depend on credit rating tools and services\u0000to help them predict the ability of creditors to meet financial persuasions.\u0000Conventional credit rating is broadly categorized into two classes namely: good\u0000credit and bad credit. This approach lacks adequate precision to perform credit\u0000risk analysis in practice. Related studies have shown that data-driven machine\u0000learning algorithms outperform many conventional statistical approaches in\u0000solving this type of problem, both in terms of accuracy and efficiency. The\u0000purpose of this paper is to construct and validate a credit risk assessment\u0000model using Linear Discriminant Analysis as a dimensionality reduction\u0000technique to discriminate good creditors from bad ones and identify the best\u0000classifier for credit assessment of commercial banks based on real-world data.\u0000This will help commercial banks to avoid monetary losses and prevent financial\u0000crisis","PeriodicalId":501128,"journal":{"name":"arXiv - QuantFin - Risk Management","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141737936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Upper Comonotonicity and Risk Aggregation under Dependence Uncertainty 依赖性不确定性下的上协整性和风险聚合

arXiv - QuantFin - Risk Management Pub Date : 2024-06-27 DOI: arxiv-2406.19242

Corrado De Vecchi, Max Nendel, Jan Streicher

{"title":"Upper Comonotonicity and Risk Aggregation under Dependence Uncertainty","authors":"Corrado De Vecchi, Max Nendel, Jan Streicher","doi":"arxiv-2406.19242","DOIUrl":"https://doi.org/arxiv-2406.19242","url":null,"abstract":"In this paper, we study dependence uncertainty and the resulting effects on\u0000tail risk measures, which play a fundamental role in modern risk management. We\u0000introduce the notion of a regular dependence measure, defined on multi-marginal\u0000couplings, as a generalization of well-known correlation statistics such as the\u0000Pearson correlation. The first main result states that even an arbitrarily\u0000small positive dependence between losses can result in perfectly correlated\u0000tails beyond a certain threshold and seemingly complete independence before\u0000this threshold. In a second step, we focus on the aggregation of individual\u0000risks with known marginal distributions by means of arbitrary nondecreasing\u0000left-continuous aggregation functions. In this context, we show that under an\u0000arbitrarily small positive dependence, the tail risk of the aggregate loss\u0000might coincide with the one of perfectly correlated losses. A similar result is\u0000derived for expectiles under mild conditions. In a last step, we discuss our\u0000results in the context of credit risk, analyzing the potential effects on the\u0000value at risk for weighted sums of Bernoulli distributed losses.","PeriodicalId":501128,"journal":{"name":"arXiv - QuantFin - Risk Management","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141529634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Merton's Default Risk Model for Public Company 上市公司的默顿违约风险模型

arXiv - QuantFin - Risk Management Pub Date : 2024-06-26 DOI: arxiv-2406.18121

Battulga Gankhuu

引用次数: 0