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arXiv research

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.

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48 results for model risk management

Paper introduces a framework for managing cyber risk with insurance and cybersecurity models.

problem Pervasive challenges in managing cyber risk, especially for capital allocation.
method Combines insurance frequency-severity models with cybersecurity cascade models for comprehensive cyber risk assessment. Facilitates informed capital allocation through a two-pillar framework.
result Demonstrates the necessity of comprehensive cost-benefit analysis for budget-constrained companies.

Paper discusses how financial institutions' model risk management can benefit academic research.

problem Improving academic research process and mitigating limitations.
method Adopting financial institutions' model risk management practices.
result Lessons from financial institutions can enhance academic research reliability.

Paper introduces RiskEmbed, a finetuned model for financial risk management.

problem Improving retrieval accuracy in financial question-answering systems.
method Curated dataset and finetuned BERT model for financial domain.
result RiskEmbed significantly outperforms general-purpose and financial embedding models.

This research develops a dynamic risk management system for industrial companies.

problem Risk assessment and management in industrial enterprises.
method Qualitative and quantitative analysis, systematic risk classification, dynamic system development.
result Effective risk management strategies formed through dynamic risk management system and risk assessment methods.

Adaptive Bernstein copulas improve risk management by preventing overfitting and reducing simulation effort.

problem Overfitting and high simulation effort in estimating dependence models.
method Constructive approach to Bernstein copulas with an admissible discrete skeleton.
result Comparison of different copula approaches in risk management shows improved accuracy and efficiency.

Third part of a study on liquidity risk in asset management, focusing on managing the asset-liability liquidity risk.

problem Managing the asset-liability liquidity risk in asset management.
method Develops a methodological and practical framework for liquidity stress testing programs.
result Proposes measurement, management, and monitoring tools for controlling the liquidity gap.

Study optimizes natural resource harvesting under model uncertainty using risk measures.

problem Optimal harvesting policy selection for natural resources under model uncertainty.
method Investigated using neoclassical growth model dynamics and convex risk measures, specifically Fréchet risk measures.
result Robust harvesting strategies quantifying operational and marginal risk under model uncertainty.

This paper explores portfolio management strategies to maximize alpha and minimize beta.

problem Maximizing returns while minimizing risk in investment portfolios.
method Examines asset allocation, diversification, active management, and risk management strategies.
result Combining these strategies optimizes portfolio performance.

Financial institutions face new model risks with AI, requiring enhanced model risk management.

problem New model risks from Generative AI applications in financial institutions.
method Enhanced model risk framework with additional testing and controls.
result Financial institutions need to enhance their model risk management for Generative AI applications.

This research proposes methods to model and assess liability liquidity risk in asset management.

problem Lack of standardized models for liability liquidity risk in asset management.
method Statistical models, zero-inflated models, aggregate and individual-based approaches, and factor models.
result Developed mathematical and statistical approaches to estimate and assess redemption shocks.

The paper proposes a new model using financial big data to improve portfolio risk analysis.

problem Addressing potential information loss in portfolio risk measurement.
method Uses financial big data to incorporate out-of-target-portfolio information and overcomes the curse of dimensionality.
result The use of financial big data improves small portfolio risk analysis.

Simplified approach to portfolio risk management and hedging in practice.

problem Challenges in applying academic portfolio risk management and hedging in real-world business settings.
method A straightforward approach using convex optimization and quadratic programming.
result Demonstrates how to solve portfolio risk management and hedging problems with CVXOPT.

The paper examines the feasibility of managing aggregate cyber-risk in IoT environments.

problem Determining sustainable conditions for providing aggregate cyber-risk coverage.
method Developed a rigorous general theory and validated it with real data.
result Conditions for sustainable aggregate cyber-risk management under heavy-tailed distributions.

Limited liability reduces leveraged risk in loan portfolio management models.

problem The impact of limited liability on risk in loan portfolio management models is not well understood.
method Formulated four models to analyze the effect of limited liability on risk and return in loan portfolio management.
result Including limited liability in loan portfolio management models produces better results in minimizing risk and maximizing expected return.

Myopic optimization outperforms reinforcement learning in portfolio management, leading to lower returns and higher risks.

problem Reinforcement learning strategies in portfolio management yield lower or negative returns and higher risks compared to myopic optimization.
method Modeling execution/liquidation frictions with mark-to-market accounting, using Malliavin calculus to derive policy gradients and risk shadow price, and quantifying phantom profit.
result Myopic optimization outperforms reinforcement learning in portfolio management, leading to better returns and lower risks.

Study finds more flood risk strategies can improve outcomes in NYC.

problem Managing future flood risks with complex models.
method Used an intermediate complexity model to analyze flood risk strategies.
result More combinations of risk mitigation strategies expand the solution set and improve outcomes.

A new method prioritizes project risks using Monte Carlo Simulation.

problem Determining the relative importance of project risks.
method Monte Carlo Simulation (MCS) for quantitative prioritization.
result Differentiates critical risks based on their impact on project duration and cost.

The paper examines variable annuities pricing and risk management using the Black-Scholes model and identifies key risk drivers.

problem Model risk in pricing and managing variable annuities using the Black-Scholes model.
method Derives a model-free decomposition of variable annuity prices and investigates hedging strategies.
result The spot price risk can always be eliminated by the BS-based hedging strategy, but there is gradual slippage and instantaneous leakage.

Paper introduces a new method for risk-sensitive investment management using RL.

problem Risk-sensitive portfolio management with unknown model parameters.
method Combines RL and risk-sensitive stochastic control with Gaussian perturbations for exploration.
result Endogenous relative-entropy regularization and optimal investment strategy derived.

Study finds risk management significantly improves pension scheme efficiency in Kenya.

problem Improving efficiency of pension schemes in Kenya.
method Panel data analysis of 128 pension schemes from 2015-2021.
result Risk management significantly mediates the relationship between corporate governance and pension scheme efficiency.

FE-GAN improves VaR and ES estimation in financial risk management.

problem Improving VaR and ES estimation in financial risk management.
method Feature-Enriched Generative Adversarial Networks (FE-GAN) with specialized models like WGAN and Tail-GAN.
result FE-GAN significantly outperforms traditional GANs in VaR and ES estimation.

GAICF proposes a framework for managing generative AI risks in banking.

problem Generative AI's impact on financial decision-making and governance.
method SR 26-2-compatible governance framework for generative AI.
result GAICF aligns generative AI practices with SR 26-2 supervisory expectations.

We generalize Quasi-Linear Means by restricting to the tail of the risk distribution and show that this can be a useful quantity in risk management since it comprises in its general form the Value at Risk, the Tail Value at Risk and the Entropic Risk Measure in a unified way. We then investigate the fundamental propert…

2019-02-19abs ↗pdf ↗

Research evaluates three risk models for portfolio construction during market downturns.

problem Challenges in constructing quantitative portfolios using statistical risk models.
method Three statistical risk models tested on 1,000 stocks across four periods.
result Models consistently outperform market returns in various crises.

Paper proposes a natural hedging framework with graphical assessment for longevity risk management.

problem Lack of a unified framework for natural hedging and graphical risk assessment.
method Structured natural hedging framework integrated with a graphical risk metric.
result Demonstrates flexibility, interpretability, and practical value for longevity risk management.

ANADDH uses deep learning to improve volatility risk management.

problem Traditional Vega hedging strategies are inadequate for rapidly changing markets.
method Combines distributional reinforcement learning with adaptive Nesterov acceleration.
result Significant performance gains over existing hedging techniques.

The paper discusses the importance of infinite-mean models in finance and risk management.

problem Classic statistical models assume finite mean or variance, which is not suitable for heavy-tailed data.
method Discussion and recent results on infinite-mean models in economics and finance.
result Classic statistical results for finite-mean models often fail or flip for infinite-mean models.

Study uses generative models to assess credit risk and determine loan sizes in e-commerce supply chain finance.

problem Credit risk assessment and loan size determination for small- and medium-sized sellers in e-commerce supply chain finance.
method Proposes a unified framework using Quantile-Regression-based Generative Metamodeling (QRGMM) integrated with Deep Factorization Machines (DeepFM) to capture complex covariate interactions in e-commerce sales data.
result Validates the model's efficacy for credit risk assessment and loan size determination on synthetic and real-world data.

Optimizes pension fund management under funding risks.

problem Managing DB pension fund under underfunded and overfunded conditions.
method Stochastic model with Ornstein-Uhlenbeck interest rate, geometric Brownian motion for benefits, and cash, bond, stock investments.
result Optimal wealth process, portfolio, and efficient frontier obtained under various tolerance levels for solvency risk.

This report was originally written as an industry white paper on Hedge Funds. This paper gives an overview to Hedge Funds, with a focus on risk management issues. We define and explain the general characteristics of Hedge Funds, their main investment strategies and the risk models employed. We address the problems in H…

2009-04-17abs ↗pdf ↗