New method corrects Markowitz variance for trading volume fluctuations.
problem Incorrect risk estimates from Markowitz variance in trading environments.
method Modeling portfolio variance based on trade volume fluctuations.
result Market-based variance can significantly differ from Markowitz variance.
Market-based asset price probability depends on trade volumes and values, improving forecasts and reliability.
problem Limited accuracy of frequency-based asset price statistical moments.
method Derive market-based variance and 3rd statistical moment from trade values and volumes, accounting for trade volume randomness.
result Market-based statistical moments improve price probability forecasts and reliability.
Market-based portfolio variance measures risks using trade data.
problem Measuring portfolio risks using traditional methods ignores trade volume randomness.
method Uses time series of trades with securities and portfolio to assess variance.
result Portfolio variance can be decomposed into securities' contributions, accounting for trade volume randomness.
The study challenges the reliability of VaR due to market randomness.
problem Reliability and accuracy of VaR predictions are compromised by market randomness.
method Introduces market-based probabilities of price and return, dependent on trade values and volumes.
result Market-based price volatility is more accurate than frequency-based VaR predictions.
The paper examines how market trade values and volumes affect price autocorrelation.
problem Understanding the impact of market trade values and volumes on price autocorrelation.
method Derives the dependence of price statistical moments and volatility on trade values and volumes, and assesses statistical moments and correlations by conventional frequency-based probabilities.
result Highlights the impact of market trade randomness on price statistical moments and autocorrelation.
Improved market state classification for risk assessment.
problem Classifying financial market states for better risk assessment.
method Modified selection criteria for market states, clustering optimization, and visualization of correlation matrices.
result Statistically significant results in SP 500 and Nikkei 225 markets.
This paper introduces a new market-based carbon risk measure for portfolio optimization.
problem The challenge of measuring and managing carbon risk in investment portfolios.
method Develops a market-based carbon risk measure and applies it to minimum variance portfolio construction.
result Market-based carbon risk measures can complement fundamental-based approaches in portfolio optimization.
The paper explores how market-based returns depend on past trade values.
problem Improving accuracy in forecasting market-based average and volatility of returns.
method Derives the dependence of market-based volatility and higher statistical moments of returns on statistical moments and correlations of current and past trade values.
result Market-based statistical moments can be approximated by a finite number of moments, improving forecast reliability.
The study proposes a framework to assess sustainability of firms using fund-level classifications and portfolio holdings.
problem To capture market-based sustainability assessments of firms.
method Exploiting fund-level sustainability classifications and granular portfolio holdings to construct Market-Implied Sustainability (MIS) scores.
result MIS scores capture sustainability dimensions different from conventional ESG ratings and improve portfolio performance.
The paper modifies asset pricing models using Taylor series expansions and market-based averages.
problem Improving asset pricing models to better reflect market dynamics.
method Derives new pricing equations using Taylor series expansions and market-based averages.
result New expressions for asset prices and volatilities derived from market data.
OpenAlpha validates decentralized capital strategies using game theory and market aggregation.
problem Decentralized capital management's lack of trust-minimised, adaptive deployment.
method Game-theoretic validation, adversarial auditing, market-based belief aggregation.
result Confidence scores from validation phases inform capital allocation rules.
We consider the problem of belief aggregation: given a group of individual agents with probabilistic beliefs over a set of uncertain events, formulate a sensible consensus or aggregate probability distribution over these events. Researchers have proposed many aggregation methods, although on the question of which is be…
A key issue in the estimation of energy hedges is the hedgers' attitude towards risk which is encapsulated in the form of the hedgers' utility function. However, the literature typically uses only one form of utility function such as the quadratic when estimating hedges. This paper addresses this issue by estimating an…
The aim of this paper is to determine the Value at Risk (VaR) of the portfolio consisting of long positions in foreign currencies on an emerging market. Basing on empirical data we restrict ourselves to the case when the tail parts of distributions of logarithmic returns of these assets follow the power laws and the lo…
Value adjustment of uncollateralized trades is determined within a risk-neutral pricing framework. When hedging such trades, investors cannot freely trade protection on their own name, thus facing an incomplete market. This fact is reflected in the non-uniqueness of the pricing measure, which is only constrained by the…
We describe how the market-based average and volatility of the "actual" return, which the investors gain within their market sales, depend on the statistical moments, volatilities, and correlations of the current and past market trade values. We describe three successive approximations. First, we derive the dependence …
Current economic theories miss most of economic dynamics.
problem Accuracy of economic theories and policies depend on economic variables and processes.
method Identify and analyze overlooked economic variables and processes.
result Many economic variables and processes not accounted for in current theories.
Enhances early risk assessments for pediatric outcomes using contrastive learning.
problem Improving risk assessments in early stages of pediatric development.
method Contrastive multi-modal framework that treats each time window as a distinct modality, training on all available data.
result Consistent improvements in early-stage risk assessments validated on real-world tasks.
Bayesian networks improve product risk assessment by handling uncertainty and causality.
problem Limited handling of uncertainty and inability to incorporate causal explanations in existing methods.
method Bayesian Networks (BNs) for improved systematic product risk assessment.
result BN approach provides more powerful and flexible risk assessments.
Unified framework for CVA sensitivities, hedging, and risk assessment.
problem Computing and managing Credit Value Adjustment (CVA) sensitivities and risks.
method Probabilistic machine learning and refined regression on simulated data, validated by Monte Carlo methods.
result Identification of optimal sensitivities for practical tasks like hedging and risk assessment.
New method assesses financial and cyber risks under uncertainty.
problem Uncertainty in risk assessment for financial and cyber systems.
method Combines stochastic approximation and distorted mix method to compute worst case average value at risk.
result Efficient algorithm for tail uncertainty in multivariate distributions.
Paper proposes model to assess financial risk of grid-ignited wildfires.
problem Financial risk and solvency threats from grid-ignited wildfires.
method Integrated model to evaluate damage costs and risk levels.
result Identifies high-risk areas for preemptive actions.
Unified market-based description of returns and variances of trades.
problem Market-based variance of trades and market portfolio.
method Unified market-based approach to describe returns and variances of trades and market portfolio.
result Market-based variance accounts for random volumes of trades and differs from Markowitz's portfolio variance.
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.
Network theory assesses systemic risk in the insurance sector.
problem Detecting critical insurance companies in systemic risk.
method Complex network approach with weighted effective resistance centrality.
result Identifies companies with significant influence on network robustness.
We investigate the probability distributions of the recurrence intervals τ between consecutive 1-min returns above a positive threshold q>0 or below a negative threshold q<0 of two indices and 20 individual stocks in China's stock market. The distributions of recurrence intervals for positive and negative thresho…
Optimizes risk assessment tools using mixed-integer programming.
problem Challenges in healthcare risk assessment due to label scarcity and asymmetric misclassification costs.
method Jointly optimizes scoring weights and category thresholds via mixed-integer programming (MIP).
result Prevents label-scarce category collapse and achieves more accurate risk categorization.
Paper proposes a new model to assess risks in energy storage systems considering both exogenous and endogenous uncertainties.
problem Current risk assessment ignores the stochastic nature of energy storage availability.
method Data-driven unified model with exogenous and endogenous uncertainty description for four types of generic energy storage.
result Comparative results show more severe risks for endogenous uncertainty, suggesting new strategies for system operators.
Ownership cost calculation plays an important role in optimal operation of distributed energy resources (DERs) and microgrids (MGs) in the future power system, known as smart grid. In this paper, a general framework for ownership cost calculation is proposed using uncertainty and risk analyses. Four ownership cost calc…
Large corporate credit models may be adapted for small business risk assessment.
problem Limited data and lack of credit analysts for small businesses.
method Adapting large corporate credit risk models for small businesses.
result Adapted models can predict small business credit risk effectively.
Study combines quantum and classical deep learning for better credit risk assessment.
problem Enhancing accuracy and efficiency in credit risk evaluation.
method Hybrid Quantum-Classical Deep Neural Network for Row-Type Dependent Predictive Analysis.
result Proposed framework enhances predictive models for different loan categories.
The paper derives market-based correlations between asset prices and returns.
problem Market assumptions of constant trade volumes and past values are inaccurate.
method Derives expressions of correlations based on statistical moments and trade volumes.
result Market-based correlations are essential for traders, banks, and funds.
Enhances Transformers for better risk assessment in finance.
problem Transformer models lack sensitivity to extreme financial losses.
method Integrates Loss-at-Risk function with Value at Risk (VaR) and Conditional Value at Risk (CVaR).
result Improves risk prediction and management in financial datasets.
Fast risk assessment for autonomous vehicles using learned agent futures.
problem Risk assessment for autonomous vehicles given probabilistic predictions of other agents' futures.
method Non-sampling based methods using deep neural networks for probabilistic predictions, with Gaussian and non-Gaussian mixture models for agent positions and controls.
result Effective risk assessment for low probability events using learned models of agent futures.
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.
TinyXRA assesses financial risks from 10-K reports using a lightweight transformer model.
problem Comprehensive risk assessment from financial reports, distinguishing between upside and downside risk.
method Lightweight transformer model with dynamic attention, incorporating skewness, kurtosis, and Sortino ratio.
result State-of-the-art predictive accuracy and transparent risk assessments.
Study examines cryptocurrency risk spillover effects before and after pandemic.
problem Analyzing risk propagation among cryptocurrencies during extreme events.
method Asymmetric breakpoint approach and network analysis.
result Cryptocurrency risk spillover effect increased during pandemic.
The paper identifies and critiques problems with risk matrices using ordinal scales.
problem Problems with risk matrices using ordinal scales.
method Overview of risk assessment process, explanation of fallacies, and suggestions for improvement.
result The paper proposes avoiding risk matrices and using fully quantitative methods instead.
Neural networks assess asset-liability risk over time.
problem Challenging valuation of portfolios with complex products.
method Neural network approach for conditional portfolio valuation.
result Effective risk assessment for banking and insurance portfolios.
The study examines how market trade randomness influences price and return volatility.
problem The accuracy of predicting market-based volatilities and macroeconomic variables is limited.
method Analyzes time series of trade values and volumes, and develops econometric methodologies for predicting volatilities.
result Current macroeconomic models underestimate the accuracy of predicting market-based volatilities and macroeconomic variables.
The paper introduces a new risk assessment framework using φ-divergence.
problem Assessing risk and decision-making in uncertain conditions.
method Introduces a novel framework called the φ-Divergence Quadrangle.
result Provides a more nuanced understanding of risk through φ-divergence.
Paper offers a fast method to assess DeFi liquidation risk.
problem Assessing liquidation risk in DeFi stablecoin lending.
method Modeling collateral exchange rate as zero-drift geometric Brownian motion.
result Derives an exact formula for liquidation probability.
Paper assesses risks of stablecoins, from lending to business-to-business.
problem Credit risks in decentralized stablecoin issuance.
method Examines mechanisms, risks, and mitigation strategies at each layer.
result Potential for scaling stablecoins while maintaining systemic health.
Paper introduces risk assessment for contextual bandits without experiments.
problem Evaluate policies using logged data in context bandits.
method Lipschitz risk functionals and Off-Policy Risk Assessment (OPRA) framework.
result OPRA provides finite sample guarantees for various risk estimates.
Risk, including economic risk, is increasingly a concern for public policy and management. The possibility of dealing effectively with risk is hampered, however, by lack of a sound empirical basis for risk assessment and management. The paper demonstrates the general point for cost and demand risks in urban rail projec…
Model assesses credit risk using behavioral data from Experian and Bank of Italy.
problem Improving credit risk assessment in financial institutions.
method Statistical and machine learning techniques applied to behavioral data from Experian and Bank of Italy.
result Demonstrates transferability of the model from private to central data.
Dynamic risk assessment method for WUI fires improves upon static frameworks.
problem Static risk assessment methods fail to capture dynamic changes in WUI fire risks.
method Dynamic evaluation matrix, grey incidence analysis, optimization model.
result The proposed method effectively captures dynamic risk evolution patterns.
Introduces factor risk measures to assess risk relative to multiple factors.
problem Measuring risk relative to multiple factors.
method Introduces a double-argument mapping as a risk measure to assess risk relative to a vector of factors.
result Characterizes various types of factor risk measures including distortion, quantile, linear, and coherent measures.