The financial crisis offers new business opportunities in heritage management.
problem Financial institutions' weakened financial condition due to fluctuating real estate property prices.
method Proactive management and stakeholder cooperation to stabilize and optimize properties.
result Properties can serve as a solid base for new business and investment opportunities.
Paper tackles curve pattern identification from fragmented cultural heritage objects.
problem Identify full design of curve patterns from fragmented cultural heritage objects.
method Two-stage matching algorithm combining template matching and CNN re-ranking.
result Proposed algorithm outperforms traditional methods in identifying curve patterns from fragmented objects.
We outline a framework which generalizes Felix Klein's Erlanger Programm which he announced in 1872 after exchanging ideas with Sophus Lie.
Surveying isoparametric hypersurfaces in spheres, focusing on Élie Cartan's techniques.
problem Classifying isoparametric hypersurfaces in spheres.
method Historical survey and focus on Élie Cartan's techniques.
result Attention to Élie Cartan's techniques in the case of four principal curvatures.
A hybrid scheme uses GAs and DL for tile panel reconstruction.
problem Reconstructing Portuguese tile panels with real-world effects.
method Enhanced GA-based puzzle solver with novel DLCM.
result 82% accuracy for tile reconstruction compared to 3.5% for best known method.
Shifu2 discovers advisor-advisee relationships in collaboration networks.
problem Discovering hidden advisor-advisee relationships in scientific collaboration networks.
method Network Representation Learning (NRL) model, considering both network structure and node/edge semantics.
result Improved stability and effectiveness compared to state-of-the-art methods.
Paper improves deep point cloud compression techniques.
problem Efficiently compressing 3D point cloud data for various applications.
method Integrates scale hyperprior model, deeper transforms, focal loss, and optimal thresholding.
result Achieves significant BD-PSNR gains over existing methods.
MAntRA combines machine learning and Bayesian methods for time-dependent reliability analysis of unknown systems.
problem Time-dependent reliability analysis of systems with unknown governing physics.
method Combines machine learning, Bayesian statistics, and stochastic integration to discover and analyze SDEs from data.
result Demonstrates the effectiveness of MAntRA on three numerical examples, indicating its potential for in-situ and heritage structure analysis.
New method controls bias in training data for fair outcomes.
problem Ensuring equal treatment between different groups in machine learning.
method Contrastive information estimation to control mutual information between representations and protected attributes.
result Our method provides strong theoretical guarantees on the parity of any downstream algorithm.
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.
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.
The basic financial purpose of a firm is to maximize its value. An inventory management system should also contribute to realization of this basic aim. Many current asset management models currently found in financial management literature were constructed with the assumption of book profit maximization as basic aim. H…
Study finds Indian mutual funds adjust cash holdings based on inflows, impacting stock purchases.
problem Active liquidity management by mutual funds in India.
method Examined cash holdings and stock purchases of Indian equity mutual funds.
result Funds with active liquidity choices outperform, highlighting the importance of this strategy.
Framework for managing cyber risks in networks.
problem Managing systemic cyber risks in digital networks.
method Three components: acceptable configurations, risk mitigation interventions, and cost function.
result Effective decision-making for network resilience.
PyCaMa simplifies cash management with Python.
problem Optimal cash management with multiple bank accounts.
method Linear programming for multiobjective cash management.
result Derives optimal policies for cost and risk.
Research identifies risks in selecting project managers for civil engineering projects.
problem Lack of awareness of project manager selection criteria and associated risks.
method Combined ANP-FMEA approach for risk analysis.
result ANP-FMEA model identifies more significant risks than traditional FMEA.
Deep learning improves portfolio management by optimizing asset weights.
problem Traditional portfolio managers are outperformed by deep learning models in trading.
method Proposes a deep reinforcement learning portfolio manager that allocates weights to assets.
result The proposed portfolio manager outperforms conventional managers in risk-adjusted returns.
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.
The paper identifies three types of classic texts in megaproject management.
problem Does megaproject management have classic texts?
method Identifying and categorizing three types of classic texts: conventional, Kuhnian, and citation classics.
result Citation classics exist and perform well compared to other management literature.
The paper defines successful active management and introduces a framework.
problem The elusive criteria for successful active management in the literature.
method Introducing definitions of key concepts and a logically coherent evaluation framework.
result A strong defense of active management emerges through the defined concepts.
Study finds managers' tenure and education influence their choice between in-court and out-of-court restructuring.
problem Exploring managers' characteristics and their impact on restructuring decisions.
method Empirical investigation using upper echelons theory and data from 342 managers of French firms.
result Managers with longer tenure and higher education levels prefer private restructuring over court involvement.
The paper fits cash management models to data using stochastic and linear programming.
problem Cash flow probability distribution assumptions in cash management models are relaxed.
method Stochastic and linear programming to fit models to data.
result A small random sample of data is sufficient to fit bound-based models.
Decision tool helps manage biofouling risks for ships in the Baltic Sea.
problem Biofouling of ships causes environmental and economic issues.
method Bayesian networks to identify biofouling management strategies.
result Optimal biofouling management includes biocidal-free coating and in-water cleaning.
AI predicts employee attrition to prevent turnover.
problem Predicting and preventing employee attrition.
method Ensemble classification and Linear Regression models.
result Predicts employee attrition with over 91% accuracy.
Model cash management under ambiguity using maxmin preferences and diffusion.
problem Optimizing cash reserves in the presence of ambiguity.
method Singular control model with maxmin preferences, verified using Dynkin games.
result Higher expected costs and narrower inaction region under increased ambiguity.
This review classifies electricity price models for risk management.
problem Choosing suitable models for risk management in electricity markets.
method Classification of models based on their ability to represent price behavior.
result Helps users select appropriate models for risk management.
This research reviews reinforcement learning for optimizing building energy management.
problem Optimizing energy utilization in building management systems.
method Comprehensive review of reinforcement learning applications in building energy management.
result Challenges and future directions in reinforcement learning for building energy management.
Report assesses Edinburgh tram project's risk management.
problem Projects often exceed costs and timelines, underperforming intended benefits.
method Describes and evaluates risk assessment and management for the Edinburgh tram.
result Careful consideration of cost, schedule, and benefit risks is crucial for megaprojects.
The document proposes a model to measure project risk management maturity.
problem The rapid change in the global environment makes risk management crucial for project success.
method Develops a maturity model to assess organizations' risk management capabilities.
result Measures the effectiveness of organizations in managing project risks.
Study improves machine learning for long-term financial portfolio management.
problem Machine learning precision declines with long-term data.
method Data augmentation using multiple time scales and learning data.
result Generalization performance can be maintained for long-term tasks.
Paper proposes real-time risk metrics for stablecoin protocols.
problem Lack of risk management frameworks for stablecoins.
method Developed two risk metrics: capitalization and liquidity.
result Demonstrated practical benefits of real-time on-chain data.
Enhances portfolio management with RL, considering transaction costs and short selling.
problem Lack of practical aspects in RL for portfolio management.
method Proposes a general RL framework for asset management with continuous weights, short selling, and relevant features. Compares PGAC, PPO, and ES algorithms in a simulated environment with transaction costs.
result Demonstrates advantages of RL algorithms in real-life asset management scenarios.
The paper analyzes portfolio management in the Heston model, proposing new strategies.
problem Investment performance influenced by asset diversity and cash inclusion.
method Monte Carlo simulations in the Heston model, MACD and RSI technical analysis.
result New portfolio management strategies based on MACD and RSI.
A fund manager invests both the fund's assets and own private wealth in separate but potentially correlated risky assets, aiming to maximize expected utility from private wealth in the long run. If relative risk aversion and investment opportunities are constant, we find that the fund's portfolio depends only on the fu…
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.
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.
This paper provides a ML framework for diabetes prediction and care management.
problem Diabetes prediction and care management challenges in real-world healthcare.
method Illustrates a Machine Learning framework for T2DM prediction and risk stratification.
result ML models align with physician's disease management steps.
Banks must manage their trading books, not just value them. Pricing includes valuation adjustments collectively known as XVA (at least credit, funding, capital and tax), so management must also include XVA. In trading book management we focus on pricing, hedging, and allocation of prices or hedging costs to desks on an…
The paper introduces deep learning for ALM, enhancing asset and liability management.
problem Optimizing asset and liability management for treasurers and other applications.
method Deep learning applied to ALM for optimal decision making.
result Enhanced ALM approach for better asset and liability management.
The basic financial purpose of an enterprise is maximization of its value. Trade credit management should also contribute to realization of this fundamental aim. Many of the current asset management models that are found in financial management literature assume book profit maximization as the basic financial purpose. …
Cash management is concerned with optimizing the short-term funding requirements of a company. To this end, different optimization strategies have been proposed to minimize costs using daily cash flow forecasts as the main input to the models. However, the effect of the accuracy of such forecasts on cash management pol…
Study optimizes nuclear power plant decommissioning risk management.
problem Optimizing risk management for decommissioning nuclear power plants.
method Numerical stochastic optimization approach linking risk aversion to an optimization problem.
result Optimal strategy involves de-risking similar to a concave strategy.
Deep RL optimizes goal-based investing strategies.
problem Optimizing investment strategies for achieving financial goals.
method Novel deep reinforcement learning approach for goal-based investing.
result Superior performance compared to benchmarks.
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.
Optimizes fund manager's wealth with partial information on market risk.
problem Maximizing wealth with incomplete information about market risk.
method Formulated as optimization under partial information, solved via martingale method and concavification.
result Shows how learning about market risk affects optimal investment strategy.
We develop a simple stock selection model to explain why active equity managers tend to underperform a benchmark index. We motivate our model with the empirical observation that the best performing stocks in a broad market index often perform much better than the other stocks in the index. Randomly selecting a subset o…
Combines human and AI to optimize fund managers' investment decisions.
problem Improving fund managers' investment practices.
method Combines Inverse Reinforcement Learning and Reinforcement Learning.
result Improves fund managers' investment performance.
RLCache uses reinforcement learning to optimize cache management decisions.
problem Optimizing cache hit rate and storage size in computer systems.
method Designing three reinforcement learning agents for cache manager tasks and two advanced architectures.
result Reinforcement learning agents achieve higher cache hit rates and minimize storage space compared to heuristics.