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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.

168,695 papers · 148 categories

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48 results for business value

These lecture notes provide a self-contained introduction to the mathematical methods required in a Bachelor degree programme in Business, Economics, or Management. In particular, the topics covered comprise real-valued vector and matrix algebra, systems of linear algebraic equations, Leontief's stationary input-output…

2015-09-11abs ↗pdf ↗

Study evaluates sustainability of European banks using a new model.

problem Lack of a framework to evaluate sustainability of banking business models.
method Delphi-Analytic Hierarchy Process method to develop and assess the model.
result Norwegian and German banks have higher sustainability of their business models.

A microscopic model of aggregation and fragmentation is introduced to investigate the size distribution of businesses. In the model, businesses are constrained to comply with the market price, as expected by the customers, while customers can only buy at the prices offered by the businesses. We show numerically and ana…

2000-08-14abs ↗pdf ↗

Develops a Bayesian model to predict business revenue and demand.

problem Estimating revenue and demand at business facilities.
method Variational Bayesian spatial interaction model (BSIM) with scalable inference.
result BSIM outperforms competing approaches in predicting pub revenue and demand.

Study optimal reinsurance and investment to minimize drawdown risk.

problem Minimizing drawdown risk in a risk model with correlated insurance claims.
method Optimal reinsurance-investment strategy under expected value and variance premium principles, considering per-loss reinsurance and financial market investment.
result Closed-form expressions for optimal reinsurance-investment strategies and value functions.

Group Shapley evaluates feature groups in business data, improving explainability in AI.

problem Evaluating the importance of feature groups in business and economic data.
method Developed Group Shapley and a significance testing procedure based on chi-square approximation.
result Market-related variables are identified as the most influential feature group.

The paper optimizes insurer's dividend, reinsurance, and capital injection strategies for two collaborating business lines.

problem Maximizing expected total dividend payments while managing risk and preventing ruin.
method Solving the problem using a closed-form value function for optimal strategies.
result Optimal strategies include threshold dividend payout, decreasing reinsured risk, and capital injection to prevent ruin.

The paper optimizes insurance strategies for two collaborating business lines.

problem Maximizing dividends and managing risk for two collaborating business lines.
method Closed-form solutions for optimal strategies, including dividend payout, reinsurance, and capital injection.
result Optimal strategies involve pure excess-of-loss reinsurance and transferring reserves to prevent ruin.

The paper analyzes optimal dividend strategies for risky businesses, considering both periodic and extraordinary payments.

problem Maximizing dividends paid until ruin, net of transaction costs.
method Modeling cash surplus as Brownian motion, considering different types of dividends with transaction costs.
result Optimal strategies depend on business profitability and transaction costs, sometimes including liquidation.

Study optimal strategies for insurer's dividends, investments, and liabilities.

problem Maximize insurer's utility of dividend payments over an infinite horizon.
method Perturbation approach to obtain optimal strategy and value function in closed form.
result Obtained optimal strategy and value function for log and power utility.

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.

Bayesian model uses mobile data to assess business resilience after hurricanes.

problem Evaluating economic impact of extreme shocks on businesses.
method Bayesian structural time series model with mobile phone data.
result Estimates business resilience after hurricanes, revealing key characteristics.

Modeling business expansion as a stochastic control problem, the study finds that firms are incentivized to expand but may wait.

problem Optimizing business expansion under exposure constraints and opportunity costs.
method Formulated as a novel stochastic control problem combined with optimal stopping time, derived an explicit solution for exponential utility.
result Firms are incentivized to expand but may wait due to opportunity costs and other factors.

The paper analyzes systemic risk in an insurance model with multiple business lines and heterogeneous claims.

problem Analyzing systemic risk in a multi-dimensional insurance model with heterogeneous claims.
method A multi-dimensional Lévy process-based renewal risk model with pairwise asymptotic independence (PAI).
result Asymptotic formulas for tail probabilities and systemic risk measures are derived.

Machine learning predicts US and EuroZone business cycles with high accuracy.

problem Predicting the business cycle phases in US and EuroZone.
method Three machine learning approaches were compared: Multinomial Logistic Regression (MLR) achieved the best results.
result MLR achieved 65.25% accuracy for EuroZone and 75% for US in predicting business cycle phases.

We study a credit risk model which captures effects of economic interactions on a firm's default probability. Economic interactions are represented as a functionally defined graph, and the existence of both cooperative, and competitive, business relations is taken into account. We provide an analytic solution of the mo…

2005-12-16abs ↗pdf ↗

Uber optimizes marketplace levers using machine learning to improve resource allocation efficiency.

problem Optimizing budget allocation for drivers and riders to maximize business value.
method End-to-end machine learning and optimization procedure using feature store, model training, and ADMM.
result Substantially improved Uber's resource allocation efficiency through high-dimensional optimization.

The study uses CoDa to analyze family business financial ratios, highlighting methodological issues.

problem Asymmetry, non-normality, and non-linearity in financial ratios of family businesses.
method Compositional data analysis (CoDa) and classical analysis strategies.
result Results are sensitive to the methodology used, emphasizing the need for appropriate methodologies.

Study examines how business units can benefit from group cohesion under regulatory constraints.

problem Regulatory constraints limit business units' ability to form a single cohesive group.
method Defined and analyzed cohesive risk measures to minimize capital costs.
result Cohesive risk measures allow groups to achieve minimal capital costs without altering individual liabilities.

This paper studies business cycle patterns in UK sectoral output. It analyzes the distinction between white noise processes and their non-white noise counterparts in the frequency domain and further examines the associated features and patterns for the process where white noise conditions are violated. The characterist…

2010-01-26abs ↗pdf ↗